Ying Nian Wu - RankMe

314 papers A* 88A 6B 3Misc 1Journal 187Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers. CoRR Dong Liu, Yanxuan Yu, Ben Lengerich, Ying Nian Wu
2026	J	`jnl`	Enhancing TableQA through Verifiable Reasoning Trace Reward. CoRR Tung Sum Thomas Kwok, Xinyu Wang, Hengzhi He, Xiaofeng Lin, Peng Lu, Liheng Ma, Chunhe Wang, Ying Nian Wu, Lei Ding, Guang Cheng
2026	J	`jnl`	Inference-Time Rethinking with Latent Thought Vectors for Math Reasoning. CoRR Deqian Kong, Minglu Zhao, Aoyang Qin, Bo Pang, Chenxin Tao, David Hartmann, Edouardo Honig, Dehong Xu, Amit Kumar, Matthew Sarte, Chuan Li, Jianwen Xie, Ying Nian Wu
2026	J	`jnl`	MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning. CoRR Dong Liu, Yanxuan Yu, Ben Lengerich, Ying Nian Wu
2026	J	`jnl`	REAL: Regression-Aware Reinforcement Learning for LLM-as-a-Judge. CoRR Yasi Zhang, Tianyu Chen, Mingyuan Zhou, Oscar Leong, Ying Nian Wu, Michal Lukasik
2026	J	`jnl`	Training LLMs for Divide-and-Conquer Reasoning Elevates Test-Time Scalability. CoRR Xiao Liang, Zhong-Zhi Li, Zhenghao Lin, Eric Hanchen Jiang, Hengyuan Zhang, Yelong Shen, Kai-Wei Chang, Ying Nian Wu, Yeyun Gong, Weizhu Chen
2026	J	`jnl`	Training-Free Self-Correction for Multimodal Masked Diffusion Models. CoRR Yidong Ouyang, Panwen Hu, Zhengyan Wan, Zhe Wang, Liyan Xie, Dmitriy Bespalov, Ying Nian Wu, Guang Cheng, Hongyuan Zha, Qiang Sun
2025	J	`jnl`	A Human-centric Framework for Debating the Ethics of AI Consciousness Under Uncertainty. CoRR Ziheng Zhou, Haiqiang Dai, Bin Ling, Ying Nian Wu, Demetri Terzopoulos
2025	A*	`conf`	An Expressive and Self-Adaptive Dynamical System for Efficient Function Learning. ICML Chuan Liu, Chunshu Wu, Ruibing Song, Ang Li, Ying Nian Wu, Tong Geng
2025	J	`jnl`	An LLM-based Agent Simulation Approach to Study Moral Evolution. CoRR Ziheng Zhou, Huacong Tang, Mingjie Bi, Yipeng Kang, Wanying He, Fang Sun, Yizhou Sun, Ying Nian Wu, Demetri Terzopoulos, Fangwei Zhong
2025	J	`jnl`	Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction. CoRR Aishni Parab, Hongjing Lu, Ying Nian Wu, Sumit Gulwani
2025	J	`jnl`	Better Prompt Compression Without Multi-Layer Perceptrons. CoRR Edouardo Honig, Andrew Lizarraga, Zijun Frank Zhang, Ying Nian Wu
2025	J	`jnl`	Beyond Pass@1: Self-Play with Variational Problem Synthesis Sustains RLVR. CoRR Xiao Liang, Zhongzhi Li, Yeyun Gong, Yelong Shen, Ying Nian Wu, Zhijiang Guo, Weizhu Chen
2025	A*	`conf`	DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models. ICLR Ruibing Song, Chuan Liu, Chunshu Wu, Ang Li, Dongfang Liu, Ying Nian Wu, Tong Geng
2025	A*	`conf`	DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving. MICRO Chuan Liu, Chunshu Wu, Ruibing Song, Guangyan Sun, Ying Nian Wu, Yousu Chen, Ang Li, Tong Geng
2025	J	`jnl`	Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation. CoRR Tianyu Chen, Yasi Zhang, Zhendong Wang, Ying Nian Wu, Oscar Leong, Mingyuan Zhou
2025	J	`jnl`	Designing Instance-Level Sampling Schedules via REINFORCE with James-Stein Shrinkage. CoRR Peiyu Yu, Suraj Kothawade, Sirui Xie, Ying Nian Wu, Hongliang Fei
2025	A*	`conf`	Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models. ICLR Chuan Liu, Chunshu Wu, Shihui Cao, Mingkai Chen, James Chenhao Liang, Ang Li, Michael Huang, Chuang Ren, Ying Nian Wu, Dongfang Liu, Tong Geng
2025	J	`jnl`	Discrete Markov Bridge. CoRR Hengli Li, Yuxuan Wang, Song-Chun Zhu, Ying Nian Wu, Zilong Zheng
2025	J	`jnl`	Dynamic Generation of Multi-LLM Agents Communication Topologies with Graph Diffusion Models. CoRR Eric Hanchen Jiang, Guancheng Wan, Sophia Yin, Mengting Li, Yuchen Wu, Xiao Liang, Xinfeng Li, Yizhou Sun, Wei Wang, Kai-Wei Chang, Ying Nian Wu
2025	J	`jnl`	EdiVal-Agent: An Object-Centric Framework for Automated, Scalable, Fine-Grained Evaluation of Multi-Turn Editing. CoRR Tianyu Chen, Yasi Zhang, Zhi Zhang, Peiyu Yu, Shu Wang, Zhendong Wang, Kevin Lin, Xiaofei Wang, Zhengyuan Yang, Linjie Li, Chung-Ching Lin, Jianwen Xie, Oscar Leong, Lijuan Wang, Ying Nian Wu, Mingyuan Zhou
2025	J	`jnl`	Embodied Web Agents: Bridging Physical-Digital Realms for Integrated Agent Intelligence. CoRR Yining Hong, Rui Sun, Bingxuan Li, Xingcheng Yao, Maxine Wu, Alexander Chien, Da Yin, Ying Nian Wu, Zhecan James Wang, Kai-Wei Chang
2025	J	`jnl`	Energy-Driven Steering: Reducing False Refusals in Large Language Models. CoRR Eric Hanchen Jiang, Weixuan Ou, Run Liu, Shengyuan Pang, Guancheng Wan, Ranjie Duan, Wei Dong, Kai-Wei Chang, Xiaofeng Wang, Ying Nian Wu, Xinfeng Li
2025	—	`conf`	Explore the Reasoning Capability of LLMs in the Chess Testbed. NAACL (Short Papers) Shu Wang, Lei Ji, Renxi Wang, Wenxiao Zhao, Haokun Liu, Yifan Hou, Ying Nian Wu
2025	J	`jnl`	FFT-Accelerated Auxiliary Variable MCMC for Fermionic Lattice Models: A Determinant-Free Approach with O(N\log N) Complexity. CoRR Deqian Kong, Shi Feng, Jianwen Xie, Ying Nian Wu
2025	J	`jnl`	FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation. CoRR Dong Liu, Jiayi Zhang, Yifan Li, Yanxuan Yu, Ben Lengerich, Ying Nian Wu
2025	J	`jnl`	Generative Actor Critic. CoRR Aoyang Qin, Deqian Kong, Wei Wang, Ying Nian Wu, Song-Chun Zhu, Sirui Xie
2025	J	`jnl`	Gold-Medal-Level Olympiad Geometry Solving with Efficient Heuristic Auxiliary Constructions. CoRR Boyan Duan, Xiao Liang, Shuai Lu, Yaoxiang Wang, Yelong Shen, Kai-Wei Chang, Ying Nian Wu, Mao Yang, Weizhu Chen, Yeyun Gong
2025	J	`jnl`	Latent Adaptive Planner for Dynamic Manipulation. CoRR Donghun Noh, Deqian Kong, Minglu Zhao, Andrew Lizarraga, Jianwen Xie, Ying Nian Wu, Dennis W. Hong
2025	J	`jnl`	Latent Space Energy-based Neural ODEs. Trans. Mach. Learn. Res. Sheng Cheng, Deqian Kong, Jianwen Xie, Kookjin Lee, Ying Nian Wu, Yezhou Yang
2025	A*	`conf`	Latent Thought Models with Variational Bayes Inference-Time Computation. ICML Deqian Kong, Minglu Zhao, Dehong Xu, Bo Pang, Shu Wang, Edouardo Honig, Zhangzhang Si, Chuan Li, Jianwen Xie, Sirui Xie, Ying Nian Wu
2025	J	`jnl`	Learning to Rank Chain-of-Thought: An Energy-Based Approach with Outcome Supervision. CoRR Eric Hanchen Jiang, Haozheng Luo, Shengyuan Pang, Xiaomin Li, Zhenting Qi, Hengli Li, Cheng-Fu Yang, Zongyu Lin, Xinfeng Li, Hao Xu, Kai-Wei Chang, Ying Nian Wu
2025	J	`jnl`	MILR: Improving Multimodal Image Generation via Test-Time Latent Reasoning. CoRR Yapeng Mi, Hengli Li, Yanpeng Zhao, Chenxi Li, Huimin Wu, Xiaojian Ma, Song-Chun Zhu, Ying Nian Wu, Qing Li
2025	J	`jnl`	MLZero: A Multi-Agent System for End-to-end Machine Learning Automation. CoRR Haoyang Fang, Boran Han, Nick Erickson, Xiyuan Zhang, Su Zhou, Anirudh Dagar, Jiani Zhang, Ali Caner Türkmen, Cuixiong Hu, Huzefa Rangwala, Ying Nian Wu, Yuyang Wang, George Karypis
2025	A*	`conf`	Monitoring Primitive Interactions During the Training of DNNs. AAAI Jie Ren, Xinhao Zheng, Jiyu Liu, Andrew Lizarraga, Ying Nian Wu, Liang Lin, Quanshi Zhang
2025	J	`jnl`	Multi-Modal Masked Autoencoders for Learning Image-Spectrum Associations for Galaxy Evolution and Cosmology. CoRR Morgan Himes, Samiksha Krishnamurthy, Andrew Lizarraga, Srinath Saikrishnan, Vikram Seenivasan, Jonathan Soriano, Ying Nian Wu, Tuan Do
2025	J	`jnl`	Multimodal Function Vectors for Spatial Relations. CoRR Shuhao Fu, Esther Goldberg, Ying Nian Wu, Hongjing Lu
2025	J	`jnl`	Multivariate Long-term Time Series Forecasting with Fourier Neural Filter. CoRR Chenheng Xu, Dan Wu, Yixin Zhu, Ying Nian Wu
2025	A*	`conf`	On Conformal Isometry of Grid Cells: Learning Distance-Preserving Position Embedding. ICLR Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu
2025	—	`conf`	On the Analysis and Distillation of Emergent Outlier Properties in Pre-trained Language Models. NAACL (Long Papers) Tianyang Zhao, Kunwar Yashraj Singh, Srikar Appalaraju, Peng Tang, Ying Nian Wu, Li Erran Li
2025	J	`jnl`	PiKV: KV Cache Management System for Mixture of Experts. CoRR Dong Liu, Yanxuan Yu, Ben Lengerich, Ying Nian Wu, Xuhong Wang
2025	J	`jnl`	Place Cells as Position Embeddings of Multi-Time Random Walk Transition Kernels for Path Planning. CoRR Minglu Zhao, Dehong Xu, Deqian Kong, Wenhao Zhang, Ying Nian Wu
2025	J	`jnl`	Restoration Score Distillation: From Corrupted Diffusion Pretraining to One-Step High-Quality Generation. CoRR Yasi Zhang, Tianyu Chen, Zhendong Wang, Ying Nian Wu, Mingyuan Zhou, Oscar Leong
2025	J	`jnl`	Scalable Language Models with Posterior Inference of Latent Thought Vectors. CoRR Deqian Kong, Minglu Zhao, Dehong Xu, Bo Pang, Shu Wang, Edouardo Honig, Zhangzhang Si, Chuan Li, Jianwen Xie, Sirui Xie, Ying Nian Wu
2025	J	`jnl`	Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space. CoRR Hengli Li, Chenxi Li, Tong Wu, Xuekai Zhu, Yuxuan Wang, Zhaoxin Yu, Eric Hanchen Jiang, Song-Chun Zhu, Zixia Jia, Ying Nian Wu, Zilong Zheng
2025	A*	`conf`	SlowFast-VGen: Slow-Fast Learning for Action-Driven Long Video Generation. ICLR Yining Hong, Beide Liu, Maxine Wu, Yuanhao Zhai, Kai-Wei Chang, Linjie Li, Kevin Lin, Chung-Ching Lin, Jianfeng Wang, Zhengyuan Yang, Ying Nian Wu, Lijuan Wang
2025	J	`jnl`	SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning. CoRR Xiao Liang, Zhong-Zhi Li, Yeyun Gong, Yang Wang, Hengyuan Zhang, Yelong Shen, Ying Nian Wu, Weizhu Chen
2025	—	`conf`	Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts. ACL (1) Jingxuan Li, Yuning Yang, Shengqi Yang, Linfan Zhang, Ying Nian Wu
2025	A*	`conf`	Visual Agents as Fast and Slow Thinkers. ICLR Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Tong Geng, Ying Nian Wu, Yongfeng Zhang, Dongfang Liu
2024	J	`jnl`	A minimalistic representation model for head direction system. CoRR Minglu Zhao, Dehong Xu, Deqian Kong, Wenhao Zhang, Ying Nian Wu
2024	J	`jnl`	An Investigation of Conformal Isometry Hypothesis for Grid Cells. CoRR Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu
2024	A*	`conf`	Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication. NeurIPS Yunuo Chen, Tianyi Xie, Zeshun Zong, Xuan Li, Feng Gao, Yin Yang, Ying Nian Wu, Chenfanfu Jiang
2024	J	`jnl`	Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication. CoRR Yunuo Chen, Tianyi Xie, Zeshun Zong, Xuan Li, Feng Gao, Yin Yang, Ying Nian Wu, Chenfanfu Jiang
2024	J	`jnl`	DODT: Enhanced Online Decision Transformer Learning through Dreamer's Actor-Critic Trajectory Forecasting. CoRR Eric Hanchen Jiang, Zhi Zhang, Dinghuai Zhang, Andrew Lizarraga, Chenheng Xu, Yasi Zhang, Siyan Zhao, Zhengjie Xu, Peiyu Yu, Yuer Tang, Deqian Kong, Ying Nian Wu
2024	J	`jnl`	Diff-PIC: Revolutionizing Particle-In-Cell Simulation for Advancing Nuclear Fusion with Diffusion Models. CoRR Chuan Liu, Chunshu Wu, Shihui Cao, Mingkai Chen, James Chenhao Liang, Ang Li, Michael Huang, Chuang Ren, Dongfang Liu, Ying Nian Wu, Tong Geng
2024	—	`conf`	Differentiable VQ-VAE's for Robust White Matter Streamline Encodings. ISBI Andrew Lizarraga, Brandon Taraku, Edouardo Honig, Ying Nian Wu, Shantanu H. Joshi
2024	J	`jnl`	Dual-Space Optimization: Improved Molecule Sequence Design by Latent Prompt Transformer. CoRR Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu
2024	A*	`conf`	EM Distillation for One-step Diffusion Models. NeurIPS Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin P. Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
2024	J	`jnl`	EM Distillation for One-step Diffusion Models. CoRR Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
2024	J	`jnl`	Efficient and Scalable Fine-Tune of Language Models for Genome Understanding. CoRR Huixin Zhan, Ying Nian Wu, Zijun Zhang
2024	J	`jnl`	Explore the Reasoning Capability of LLMs in the Chess Testbed. CoRR Shu Wang, Lei Ji, Renxi Wang, Wenxiao Zhao, Haokun Liu, Yifan Hou, Ying Nian Wu
2024	A*	`conf`	Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching. NeurIPS Yasi Zhang, Peiyu Yu, Yaxuan Zhu, Yingshan Chang, Feng Gao, Ying Nian Wu, Oscar Leong
2024	J	`jnl`	Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching. CoRR Yasi Zhang, Peiyu Yu, Yaxuan Zhu, Yingshan Chang, Feng Gao, Ying Nian Wu, Oscar Leong
2024	—	`conf`	INTERPRET: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning. Robotics: Science and Systems Muzhi Han, Yifeng Zhu, Song-Chun Zhu, Ying Nian Wu, Yuke Zhu
2024	A*	`conf`	Image Translation as Diffusion Visual Programmers. ICLR Cheng Han, James Chenhao Liang, Qifan Wang, Majid Rabbani, Sohail A. Dianat, Raghuveer Rao, Ying Nian Wu, Dongfang Liu
2024	J	`jnl`	Image Translation as Diffusion Visual Programmers. CoRR Cheng Han, James Chenhao Liang, Qifan Wang, Majid Rabbani, Sohail A. Dianat, Raghuveer Rao, Ying Nian Wu, Dongfang Liu
2024	J	`jnl`	Inertial Confinement Fusion Forecasting via LLMs. CoRR Mingkai Chen, Taowen Wang, James Chenhao Liang, Chuan Liu, Chunshu Wu, Qifan Wang, Ying Nian Wu, Michael Huang, Chuang Ren, Ang Li, Tong Geng, Dongfang Liu
2024	J	`jnl`	InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning. CoRR Muzhi Han, Yifeng Zhu, Song-Chun Zhu, Ying Nian Wu, Yuke Zhu
2024	A	`conf`	LLM IROS Shu Wang, Muzhi Han, Ziyuan Jiao, Zeyu Zhang, Ying Nian Wu, Song-Chun Zhu, Hangxin Liu
2024	J	`jnl`	LLM3: Large Language Model-based Task and Motion Planning with Motion Failure Reasoning. CoRR Shu Wang, Muzhi Han, Ziyuan Jiao, Zeyu Zhang, Ying Nian Wu, Song-Chun Zhu, Hangxin Liu
2024	J	`jnl`	Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. CoRR Peiyu Yu, Dinghuai Zhang, Hengzhi He, Xiaojian Ma, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu
2024	A*	`conf`	Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference. NeurIPS Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu
2024	J	`jnl`	Latent Plan Transformer: Planning as Latent Variable Inference. CoRR Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu
2024	J	`jnl`	Latent Space Energy-based Neural ODEs. CoRR Sheng Cheng, Deqian Kong, Jianwen Xie, Kookjin Lee, Ying Nian Wu, Yezhou Yang
2024	A	`conf`	Learning Concept-Based Causal Transition and Symbolic Reasoning for Visual Planning. IROS Yilue Qian, Peiyu Yu, Ying Nian Wu, Yao Su, Wei Wang, Lifeng Fan
2024	A*	`conf`	Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. ICLR Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao
2024	A*	`conf`	Learning for Transductive Threshold Calibration in Open-World Recognition. CVPR Qin Zhang, Dongsheng An, Tianjun Xiao, Tong He, Qingming Tang, Ying Nian Wu, Joseph Tighe, Yifan Xing
2024	J	`jnl`	Learning the Evolution of Physical Structure of Galaxies via Diffusion Models. CoRR Andrew Lizarraga, Eric Hanchen Jiang, Jacob Nowack, Yun Qi Li, Ying Nian Wu, Bernie Boscoe, Tuan Do
2024	Misc	`conf`	Long-Term Social Interaction Context: The Key to Egocentric Addressee Detection. ICASSP Deqian Kong, Furqan Khan, Xu Zhang, Prateek Singhal, Ying Nian Wu
2024	J	`jnl`	Long-range gene expression prediction with token alignment of large language model. CoRR Edouardo Honig, Huixin Zhan, Ying Nian Wu, Zijun Frank Zhang
2024	A*	`conf`	Molecule Design by Latent Prompt Transformer. NeurIPS Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu
2024	—	`conf`	NP-NDS: A Nature-Powered Nonlinear Dynamical System for Power Grid Forecasting. LoG Chunshu Wu, Ruibing Song, Chuan Liu, Yuqing Wang, Yousu Chen, Ang Li, Dongfang Liu, Ying Nian Wu, Michael Huang, Tong Geng
2024	A*	`conf`	Neural-Symbolic Recursive Machine for Systematic Generalization. ICLR Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang
2024	A*	`conf`	No Head Left Behind - Multi-Head Alignment Distillation for Transformers. AAAI Tianyang Zhao, Kunwar Yashraj Singh, Srikar Appalaraju, Peng Tang, Vijay Mahadevan, R. Manmatha, Ying Nian Wu
2024	—	`conf`	Object-Conditioned Energy-Based Attention Map Alignment in Text-to-Image Diffusion Models. ECCV (42) Yasi Zhang, Peiyu Yu, Ying Nian Wu
2024	J	`jnl`	Object-Conditioned Energy-Based Attention Map Alignment in Text-to-Image Diffusion Models. CoRR Yasi Zhang, Peiyu Yu, Ying Nian Wu
2024	J	`jnl`	Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts. CoRR Jingxuan Li, Yuning Yang, Shengqi Yang, Yizhou Zhao, Ying Nian Wu
2024	—	`conf`	Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation. ECCV (87) Yingshan Chang, Yasi Zhang, Zhiyuan Fang, Ying Nian Wu, Yonatan Bisk, Feng Gao
2024	J	`jnl`	TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft. CoRR Qian Long, Zhi Li, Ran Gong, Ying Nian Wu, Demetri Terzopoulos, Xiaofeng Gao
2024	A*	`conf`	The motion planning neural circuit in goal-directed navigation as Lie group operator search. NeurIPS Junfeng Zuo, Ying Nian Wu, Si Wu, Wenhao Zhang
2024	J	`jnl`	Think Twice Before You Act: Improving Inverse Problem Solving With MCMC. CoRR Yaxuan Zhu, Zehao Dou, Haoxin Zheng, Yasi Zhang, Ying Nian Wu, Ruiqi Gao
2024	A*	`conf`	Threshold-Consistent Margin Loss for Open-World Deep Metric Learning. ICLR Qin Zhang, Linghan Xu, Jun Fang, Qingming Tang, Ying Nian Wu, Joseph Tighe, Yifan Xing
2024	J	`jnl`	Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory. CoRR Eric Hanchen Jiang, Yasi Zhang, Zhi Zhang, Yixin Wan, Andrew Lizarraga, Shufan Li, Ying Nian Wu
2024	J	`jnl`	Visual Agents as Fast and Slow Thinkers. CoRR Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Ying Nian Wu, Yongfeng Zhang, Dongfang Liu
2024	A*	`conf`	Visual Fourier Prompt Tuning. NeurIPS Runjia Zeng, Cheng Han, Qifan Wang, Chunshu Wu, Tong Geng, Lifu Huang, Ying Nian Wu, Dongfang Liu
2024	J	`jnl`	Visual Fourier Prompt Tuning. CoRR Runjia Zeng, Cheng Han, Qifan Wang, Chunshu Wu, Tong Geng, Lifu Huang, Ying Nian Wu, Dongfang Liu
2024	J	`jnl`	Watermarking Generative Tabular Data. CoRR Hengzhi He, Peiyu Yu, Junpeng Ren, Ying Nian Wu, Guang Cheng
2023	A*	`conf`	A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics. ICLR Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2023	A*	`conf`	A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation. NeurIPS Junfeng Zuo, Xiao Liu, Ying Nian Wu, Si Wu, Wenhao Zhang
2023	J	`jnl`	Calibration-Aware Margin Loss: Pushing the Accuracy-Calibration Consistency Pareto Frontier for Deep Metric Learning. CoRR Qin Zhang, Linghan Xu, Qingming Tang, Jun Fang, Ying Nian Wu, Joe Tighe, Yifan Xing
2023	A*	`conf`	Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models. NeurIPS Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Jianfeng Gao
2023	J	`jnl`	Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models. CoRR Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Jianfeng Gao
2023	J	`jnl`	Conformal Normalization in Recurrent Neural Network of Grid Cells. CoRR Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu
2023	J	`jnl`	Differentiable VQ-VAE's for Robust White Matter Streamline Encodings. CoRR Andrew Lizarraga, Brandon Taraku, Edouardo Honig, Ying Nian Wu, Shantanu H. Joshi
2023	A*	`conf`	Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference. ICML Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang, Pascale Fung, Ying Nian Wu
2023	J	`jnl`	Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference. CoRR Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang, Pascale Fung, Ying Nian Wu
2023	A*	`conf`	Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning. ICLR Pan Lu, Liang Qiu, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Tanmay Rajpurohit, Peter Clark, Ashwin Kalyan
2023	J	`jnl`	Energy-Based Continuous Inverse Optimal Control. IEEE Trans. Neural Networks Learn. Syst. Yifei Xu, Jianwen Xie, Tianyang Zhao, Chris L. Baker, Yibiao Zhao, Ying Nian Wu
2023	J	`jnl`	Learning Concept-Based Visual Causal Transition and Symbolic Reasoning for Visual Planning. CoRR Yilue Qian, Peiyu Yu, Ying Nian Wu, Wei Wang, Lifeng Fan
2023	A*	`conf`	Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. NeurIPS Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
2023	J	`jnl`	Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. CoRR Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
2023	A*	`conf`	Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. ICCV Jiali Cui, Ying Nian Wu, Tian Han
2023	J	`jnl`	Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. CoRR Jiali Cui, Ying Nian Wu, Tian Han
2023	A*	`conf`	Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CVPR Jiali Cui, Ying Nian Wu, Tian Han
2023	J	`jnl`	Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CoRR Jiali Cui, Ying Nian Wu, Tian Han
2023	J	`jnl`	Learning for Open-World Calibration with Graph Neural Networks. CoRR Qin Zhang, Dongsheng An, Tianjun Xiao, Tong He, Qingming Tang, Ying Nian Wu, Joseph Tighe, Yifan Xing
2023	J	`jnl`	Molecule Design by Latent Prompt Transformer. CoRR Deqian Kong, Yuhao Huang, Jianwen Xie, Ying Nian Wu
2023	A	`conf`	Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. UAI Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu
2023	J	`jnl`	Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. CoRR Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu
2023	A*	`conf`	On the Complexity of Bayesian Generalization. ICML Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He, Joshua B. Tenenbaum, Song-Chun Zhu, Ying Nian Wu, Wenjuan Han, Yixin Zhu
2023	—	`conf`	Sim2Plan: Robot Motion Planning via Message Passing Between Simulation and Reality. FTC (1) Yizhou Zhao, Yuanhong Zeng, Qian Long, Ying Nian Wu, Song-Chun Zhu
2023	J	`jnl`	Sim2Plan: Robot Motion Planning via Message Passing between Simulation and Reality. CoRR Yizhou Zhao, Yuanhong Zeng, Qian Long, Ying Nian Wu, Song-Chun Zhu
2023	J	`jnl`	Study on a hybrid algorithm combining enhanced ant colony optimization and double improved simulated annealing via clustering in the Traveling Salesman Problem (TSP). PeerJ Comput. Sci. Tan Hao, Ying Nian Wu, Zhang Jiaxing, Zhang Jing
2023	J	`jnl`	Triple Regression for Camera Agnostic Sim2Real Robot Grasping and Manipulation Tasks. CoRR Yuanhong Zeng, Yizhou Zhao, Ying Nian Wu
2022	J	`jnl`	A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering. CoRR Feng Gao, Qing Ping, Govind Thattai, Aishwarya N. Reganti, Ying Nian Wu, Prem Natarajan
2022	—	`conf`	Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. NeurReps Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu
2022	J	`jnl`	Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. CoRR Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu
2022	J	`jnl`	Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning. IEEE Trans. Pattern Anal. Mach. Intell. Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
2022	A	`conf`	Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. AISTATS Cristian I. Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
2022	J	`jnl`	Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. CoRR Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
2022	J	`jnl`	Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry. IEEE Trans. Pattern Anal. Mach. Intell. Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
2022	J	`jnl`	Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning. CoRR Pan Lu, Liang Qiu, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Tanmay Rajpurohit, Peter Clark, Ashwin Kalyan
2022	J	`jnl`	Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
2022	J	`jnl`	In situ bidirectional human-robot value alignment. Sci. Robotics Luyao Yuan, Xiaofeng Gao, Zilong Zheng, Mark Edmonds, Ying Nian Wu, Federico Rossano, Hongjing Lu, Yixin Zhu, Song-Chun Zhu
2022	J	`jnl`	Latent Diffusion Energy-Based Model for Interpretable Text Modeling. CoRR Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
2022	A*	`conf`	Latent Diffusion Energy-Based Model for Interpretable Text Modelling. ICML Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
2022	—	`conf`	Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning. ECCV (39) Chi Zhang, Sirui Xie, Baoxiong Jia, Ying Nian Wu, Song-Chun Zhu, Yixin Zhu
2022	A*	`conf`	Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion. AAAI Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, Ying Nian Wu
2022	A*	`conf`	MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC. ICLR Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2022	J	`jnl`	Neural-Symbolic Recursive Machine for Systematic Generalization. CoRR Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang
2022	J	`jnl`	On the Complexity of Bayesian Generalization. CoRR Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He, Joshua B. Tenenbaum, Song-Chun Zhu, Ying Nian Wu, Wenjuan Han, Yixin Zhu
2022	A*	`conf`	SAS: Self-Augmentation Strategy for Language Model Pre-training. AAAI Yifei Xu, Jingqiao Zhang, Ru He, Liangzhu Ge, Chao Yang, Cheng Yang, Ying Nian Wu
2022	J	`jnl`	SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing Data. CoRR Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
2022	A*	`conf`	Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering. CVPR Feng Gao, Qing Ping, Govind Thattai, Aishwarya N. Reganti, Ying Nian Wu, Prem Natarajan
2022	A*	`conf`	Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors. NeurIPS Wenhao Zhang, Ying Nian Wu, Si Wu
2021	J	`jnl`	A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics. CoRR Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2021	—	`conf`	A Model Obfuscation Approach to IoT Security. CNS Yunqi Guo, Zhaowei Tan, Kaiyuan Chen, Songwu Lu, Ying Nian Wu
2021	B	`conf`	A Study of Local Optima for Learning Feature Interactions using Neural Networks. IJCNN Yangzi Guo, Ying Nian Wu, Adrian Barbu
2021	A*	`conf`	Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance. ICRA Xu Xie, Chi Zhang, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance. CoRR Xu Xie, Chi Zhang, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	Extraction of an Explanatory Graph to Interpret a CNN. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xin Wang, Ruiming Cao, Ying Nian Wu, Feng Shi, Song-Chun Zhu
2021	A*	`conf`	Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. CVPR Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
2021	A	`conf`	Generative Text Modeling through Short Run Inference. EACL Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
2021	J	`jnl`	Generative Text Modeling through Short Run Inference. CoRR Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
2021	J	`jnl`	HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving. CoRR Sirui Xie, Xiaojian Ma, Peiyu Yu, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	Interpretable CNNs for Object Classification. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xin Wang, Ying Nian Wu, Huilin Zhou, Song-Chun Zhu
2021	A*	`conf`	Iterative Teacher-Aware Learning. NeurIPS Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	Iterative Teacher-Aware Learning. CoRR Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu
2021	A*	`conf`	Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification. ICML Bo Pang, Ying Nian Wu
2021	J	`jnl`	Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification. CoRR Bo Pang, Ying Nian Wu
2021	J	`jnl`	Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning. CoRR Chi Zhang, Sirui Xie, Baoxiong Jia, Ying Nian Wu, Song-Chun Zhu, Yixin Zhu
2021	A*	`conf`	Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. AAAI Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
2021	J	`jnl`	Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. CoRR Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
2021	A*	`conf`	Learning Energy-Based Models by Diffusion Recovery Likelihood. ICLR Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
2021	J	`jnl`	Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns. IEEE Trans. Pattern Anal. Mach. Intell. Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2021	A*	`conf`	Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis. CVPR Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, Ying Nian Wu
2021	J	`jnl`	Mining Interpretable AOG Representations From Convolutional Networks via Active Question Answering. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Jie Ren, Ge Huang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2021	A*	`conf`	On Path Integration of Grid Cells: Group Representation and Isotropic Scaling. NeurIPS Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu
2021	A*	`conf`	Planning on a (Risk) Budget: Safe Non-Conservative Planning in Probabilistic Dynamic Environments. ICRA Hung-Jui Huang, Kai-Chi Huang, Michal Cáp, Yibiao Zhao, Ying Nian Wu, Chris L. Baker
2021	J	`jnl`	Planning on a (Risk) Budget: Safe Non-Conservative Planning in Probabilistic Dynamic Environments. CoRR Hung-Jui Huang, Kai-Chi Huang, Michal Cáp, Yibiao Zhao, Ying Nian Wu, Chris L. Baker
2021	J	`jnl`	Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. CoRR Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
2021	—	`conf`	Robust Transfer Learning with Pretrained Language Models through Adapters. ACL/IJCNLP (2) Wenjuan Han, Bo Pang, Ying Nian Wu
2021	J	`jnl`	Robust Transfer Learning with Pretrained Language Models through Adapters. CoRR Wenjuan Han, Bo Pang, Ying Nian Wu
2021	J	`jnl`	SAS: Self-Augmented Strategy for Language Model Pre-training. CoRR Yifei Xu, Jingqiao Zhang, Ru He, Liangzhu Ge, Chao Yang, Cheng Yang, Ying Nian Wu
2021	—	`conf`	SCRIPT: Self-Critic PreTraining of Transformers. NAACL-HLT Erik Nijkamp, Bo Pang, Ying Nian Wu, Caiming Xiong
2021	—	`conf`	SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues. ACL/IJCNLP (1) Liang Qiu, Yuan Liang, Yizhou Zhao, Pan Lu, Baolin Peng, Zhou Yu, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues. CoRR Liang Qiu, Yuan Liang, Yizhou Zhao, Pan Lu, Baolin Peng, Zhou Yu, Ying Nian Wu, Song-Chun Zhu
2021	A*	`conf`	Trajectory Prediction With Latent Belief Energy-Based Model. CVPR Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu
2021	J	`jnl`	Trajectory Prediction with Latent Belief Energy-Based Model. CoRR Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu
2021	A*	`conf`	Unsupervised Foreground Extraction via Deep Region Competition. NeurIPS Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	Unsupervised Foreground Extraction via Deep Region Competition. CoRR Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2020	J	`jnl`	A Representational Model of Grid Cells Based on Matrix Lie Algebras. CoRR Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning. ICML Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu
2020	J	`jnl`	Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning. CoRR Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu
2020	J	`jnl`	Cooperative Training of Descriptor and Generator Networks. IEEE Trans. Pattern Anal. Mach. Intell. Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense. CoRR Yixin Zhu, Tao Gao, Lifeng Fan, Siyuan Huang, Mark Edmonds, Hangxin Liu, Feng Gao, Chi Zhang, Siyuan Qi, Ying Nian Wu, Joshua B. Tenenbaum, Song-Chun Zhu
2020	A*	`conf`	Flow Contrastive Estimation of Energy-Based Models. CVPR Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu
2020	J	`jnl`	Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. CoRR Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. CoRR Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
2020	B	`conf`	Imposing implicit feasibility constraints on deformable image registration using a statistical generative model. Image Processing Yudi Sang, Xianglei Xing, Ying Nian Wu, Dan Ruan
2020	A*	`conf`	Inducing Hierarchical Compositional Model by Sparsifying Generator Network. CVPR Xianglei Xing, Tianfu Wu, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. CVPR Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. CoRR Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Energy-Based Models by Diffusion Recovery Likelihood. CoRR Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
2020	J	`jnl`	Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC. CoRR Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Latent Space Energy-Based Prior Model for Molecule Generation. CoRR Bo Pang, Tian Han, Ying Nian Wu
2020	A*	`conf`	Learning Latent Space Energy-Based Prior Model. NeurIPS Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Latent Space Energy-Based Prior Model. CoRR Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2020	—	`conf`	Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference. ECCV (6) Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. AAAI Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models. AAAI Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling. CoRR Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu
2019	J	`jnl`	A tale of two explanations: Enhancing human trust by explaining robot behavior. Sci. Robotics Mark Edmonds, Feng Gao, Hangxin Liu, Xu Xie, Siyuan Qi, Brandon Rothrock, Yixin Zhu, Ying Nian Wu, Hongjing Lu, Song-Chun Zhu
2019	J	`jnl`	Deep Unsupervised Clustering with Clustered Generator Model. CoRR Dandan Zhu, Tian Han, Linqi Zhou, Xiaokang Yang, Ying Nian Wu
2019	A*	`conf`	Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model. CVPR Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Flow Contrastive Estimation of Energy-Based Models. CoRR Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu
2019	J	`jnl`	Inducing Sparse Coding and And-Or Grammar from Generator Network. CoRR Xianglei Xing, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Interpretable CNNs. CoRR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2019	A*	`conf`	Interpreting CNNs via Decision Trees. CVPR Quanshi Zhang, Yu Yang, Haotian Ma, Ying Nian Wu
2019	J	`jnl`	Learning Deep Generative Models with Short Run Inference Dynamics. CoRR Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
2019	A*	`conf`	Learning Dynamic Generator Model by Alternating Back-Propagation through Time. AAAI Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Learning Energy-based Spatial-Temporal Generative ConvNets for Dynamic Patterns. CoRR Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2019	A	`conf`	Learning Generator Networks for Dynamic Patterns. WACV Tian Han, Yang Lu, Jiawen Wu, Xianglei Xing, Ying Nian Wu
2019	—	`conf`	Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion. ICLR (Poster) Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2019	A*	`conf`	Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model. NeurIPS Erik Nijkamp, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Learning Trajectory Prediction with Continuous Inverse Optimal Control via Langevin Sampling of Energy-Based Models. CoRR Yifei Xu, Tianyang Zhao, Chris L. Baker, Yibiao Zhao, Ying Nian Wu
2019	J	`jnl`	Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1. CoRR Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. CoRR Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
2019	A*	`conf`	Multi-Agent Tensor Fusion for Contextual Trajectory Prediction. CVPR Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris L. Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu
2019	J	`jnl`	Multi-Agent Tensor Fusion for Contextual Trajectory Prediction. CoRR Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris L. Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu
2019	J	`jnl`	Multimodal Conditional Learning with Fast Thinking Policy-like Model and Slow Thinking Planner-like Model. CoRR Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Network Transplanting (extended abstract). CoRR Quanshi Zhang, Yu Yang, Qian Yu, Ying Nian Wu
2019	J	`jnl`	Neural Architecture Search for Joint Optimization of Predictive Power and Biological Knowledge. CoRR Zijun Zhang, Linqi Zhou, Liangke Gou, Ying Nian Wu
2019	J	`jnl`	On Learning Non-Convergent Short-Run MCMC Toward Energy-Based Model. CoRR Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	On the Anatomy of MCMC-based Maximum Likelihood Learning of Energy-Based Models. CoRR Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Replicating Neuroscience Observations on ML/MF and AM Face Patches by Deep Generative Model. Neural Comput. Tian Han, Xianglei Xing, Jiawen Wu, Ying Nian Wu
2019	J	`jnl`	Representation Learning: A Statistical Perspective. CoRR Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Towards Interpretable Image Synthesis by Learning Sparsely Connected AND-OR Networks. CoRR Xianglei Xing, Tianfu Wu, Song-Chun Zhu, Ying Nian Wu
2019	A*	`conf`	Unsupervised Disentangling of Appearance and Geometry by Deformable Generator Network. CVPR Xianglei Xing, Tian Han, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract). CoRR Quanshi Zhang, Yu Yang, Ying Nian Wu
2018	J	`jnl`	A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models. CoRR Ying Nian Wu, Ruiqi Gao, Tian Han, Song-Chun Zhu
2018	A*	`conf`	Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation. NeurIPS Siyuan Huang, Siyuan Qi, Yinxue Xiao, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation. CoRR Siyuan Huang, Siyuan Qi, Yinxue Xiao, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
2018	A*	`conf`	Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching. AAAI Jianwen Xie, Yang Lu, Ruiqi Gao, Ying Nian Wu
2018	J	`jnl`	Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry. CoRR Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model. CoRR Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Explanatory Graphs for CNNs. CoRR Quanshi Zhang, Xin Wang, Ruiming Cao, Ying Nian Wu, Feng Shi, Song-Chun Zhu
2018	J	`jnl`	Interactive Agent Modeling by Learning to Probe. CoRR Tianmin Shu, Caiming Xiong, Ying Nian Wu, Song-Chun Zhu
2018	A*	`conf`	Interpretable Convolutional Neural Networks. CVPR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2018	A*	`conf`	Interpreting CNN Knowledge via an Explanatory Graph. AAAI Quanshi Zhang, Ruiming Cao, Feng Shi, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Interpreting CNNs via Decision Trees. CoRR Quanshi Zhang, Yu Yang, Ying Nian Wu, Song-Chun Zhu
2018	A*	`conf`	Learning Descriptor Networks for 3D Shape Synthesis and Analysis. CVPR Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Learning Descriptor Networks for 3D Shape Synthesis and Analysis. CoRR Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Learning Dynamic Generator Model by Alternating Back-Propagation Through Time. CoRR Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
2018	A*	`conf`	Learning Generative ConvNets via Multi-Grid Modeling and Sampling. CVPR Ruiqi Gao, Yang Lu, Junpei Zhou, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion. CoRR Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2018	B	`conf`	Learning Multi-view Generator Network for Shared Representation. ICPR Tian Han, Xianglei Xing, Ying Nian Wu
2018	J	`jnl`	Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering. CoRR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Mining deep And-Or object structures via cost-sensitive question-answer-based active annotations. Comput. Vis. Image Underst. Quanshi Zhang, Ying Nian Wu, Hao Zhang, Song-Chun Zhu
2018	J	`jnl`	Network Transplanting. CoRR Quanshi Zhang, Yu Yang, Ying Nian Wu, Song-Chun Zhu
2018	A*	`conf`	Replicating Active Appearance Model by Generator Network. IJCAI Tian Han, Jiawen Wu, Ying Nian Wu
2018	J	`jnl`	Replicating Active Appearance Model by Generator Network. CoRR Tian Han, Jiawen Wu, Ying Nian Wu
2018	J	`jnl`	Unsupervised Learning of Neural Networks to Explain Neural Networks. CoRR Quanshi Zhang, Yu Yang, Yuchen Liu, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	A Cost-Sensitive Visual Question-Answer Framework for Mining a Deep And-OR Object Semantics from Web Images. CoRR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2017	A*	`conf`	Alternating Back-Propagation for Generator Network. AAAI Tian Han, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2017	A*	`conf`	Generative Hierarchical Learning of Sparse FRAME Models. CVPR Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu
2017	A*	`conf`	Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning. AAAI Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Interactively Transferring CNN Patterns for Part Localization. CoRR Quanshi Zhang, Ruiming Cao, Shengming Zhang, Mark Edmonds, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Interpretable Convolutional Neural Networks. CoRR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Interpreting CNN knowledge via an Explanatory Graph. CoRR Quanshi Zhang, Ruiming Cao, Feng Shi, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Learning Multi-grid Generative ConvNets by Minimal Contrastive Divergence. CoRR Ruiqi Gao, Yang Lu, Junpei Zhou, Song-Chun Zhu, Ying Nian Wu
2017	A*	`conf`	Mining Object Parts from CNNs via Active Question-Answering. CVPR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Mining Object Parts from CNNs via Active Question-Answering. CoRR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2017	A*	`conf`	Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet. CVPR Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2016	A*	`conf`	A Theory of Generative ConvNet. ICML Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2016	J	`jnl`	A Theory of Generative ConvNet. CoRR Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2016	J	`jnl`	Bayesian variable selection for finite mixture model of linear regressions. Comput. Stat. Data Anal. Kuo-Jung Lee, Ray-Bing Chen, Ying Nian Wu
2016	J	`jnl`	Cooperative Training of Descriptor and Generator Networks. CoRR Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2016	J	`jnl`	Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms. CoRR Jianwen Xie, Pamela K. Douglas, Ying Nian Wu, Arthur L. Brody, Ariana E. Anderson
2016	A*	`conf`	Learning FRAME Models Using CNN Filters. AAAI Yang Lu, Song-Chun Zhu, Ying Nian Wu
2016	J	`jnl`	Learning Generative ConvNet with Continuous Latent Factors by Alternating Back-Propagation. CoRR Tian Han, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2016	J	`jnl`	Multi-Shot Mining Semantic Part Concepts in CNNs. CoRR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2016	J	`jnl`	Synthesizing Dynamic Textures and Sounds by Spatial-Temporal Generative ConvNet. CoRR Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
2015	—	`conf`	Generative Modeling of Convolutional Neural Networks. ICLR (Poster) Jifeng Dai, Ying Nian Wu
2015	J	`jnl`	Learning FRAME Models Using CNN Filters for Knowledge Visualization. CoRR Yang Lu, Song-Chun Zhu, Ying Nian Wu
2015	J	`jnl`	Learning Sparse FRAME Models for Natural Image Patterns. Int. J. Comput. Vis. Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
2015	A*	`conf`	Mining And-Or Graphs for Graph Matching and Object Discovery. ICCV Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2014	—	`conf`	Bayesian Variable Selection for Multi-response Linear Regression. TAAI Wan-Ping Chen, Ying Nian Wu, Ray-Bing Chen
2014	—	`ch.`	Cross Entropy. Computer Vision, A Reference Guide Ying Nian Wu
2014	—	`ch.`	Data Augmentation. Computer Vision, A Reference Guide Ying Nian Wu
2014	—	`ch.`	Histogram. Computer Vision, A Reference Guide Ying Nian Wu
2014	A*	`conf`	Learning Inhomogeneous FRAME Models for Object Patterns. CVPR Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
2014	J	`jnl`	Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD. NeuroImage Ariana E. Anderson, Pamela K. Douglas, Wesley T. Kerr, Virginia S. Haynes, Alan L. Yuille, Jianwen Xie, Ying Nian Wu, Jesse A. Brown, Mark S. Cohen
2014	—	`ch.`	Statistical Independence. Computer Vision, A Reference Guide Ying Nian Wu
2014	A*	`conf`	Unsupervised Learning of Dictionaries of Hierarchical Compositional Models. CVPR Jifeng Dai, Yi Hong, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
2013	A*	`conf`	Cosegmentation and Cosketch by Unsupervised Learning. ICCV Jifeng Dai, Ying Nian Wu, Jie Zhou, Song-Chun Zhu
2011	A*	`conf`	Image representation by active curves. ICCV Wenze Hu, Ying Nian Wu, Song-Chun Zhu
2011	J	`jnl`	Stochastic matching pursuit for Bayesian variable selection. Stat. Comput. Ray-Bing Chen, Chi-Hsiang Chu, Te-You Lai, Ying Nian Wu
2010	J	`jnl`	Learning Active Basis Model for Object Detection and Recognition. Int. J. Comput. Vis. Ying Nian Wu, Zhangzhang Si, Haifeng Gong, Song Chun Zhu
2010	—	`conf`	Wavelet, active basis, and shape script: a tour in the sparse land. Multimedia Information Retrieval Zhangzhang Si, Ying Nian Wu
2009	A*	`conf`	Learning mixed templates for object recognition. CVPR Zhangzhang Si, Haifeng Gong, Ying Nian Wu, Song Chun Zhu
2007	J	`jnl`	A null space method for over-complete blind source separation. Comput. Stat. Data Anal. Ray-Bing Chen, Ying Nian Wu
2007	A*	`conf`	Deformable Template As Active Basis. ICCV Ying Nian Wu, Zhangzhang Si, Chuck Fleming, Song Chun Zhu
2007	J	`jnl`	Primal sketch: Integrating structure and texture. Comput. Vis. Image Underst. Cheng-en Guo, Song Chun Zhu, Ying Nian Wu
2007	J	`jnl`	Statistical Principles in Image Modeling. Technometrics Ying Nian Wu, Jinhui Li, Ziqiang Liu, Song-Chun Zhu
2004	—	`conf`	Information Scaling Laws in Natural Scenes. CVPR Workshops Cheng-en Guo, Ying Nian Wu, Song Chun Zhu
2003	J	`jnl`	Dynamic Textures. Int. J. Comput. Vis. Gianfranco Doretto, Alessandro Chiuso, Ying Nian Wu, Stefano Soatto
2003	J	`jnl`	Modeling Visual Patterns by Integrating Descriptive and Generative Methods. Int. J. Comput. Vis. Cheng-en Guo, Song Chun Zhu, Ying Nian Wu
2003	A*	`conf`	Towards a Mathematical Theory of Primal Sketch and Sketchability. ICCV Cheng-en Guo, Song Chun Zhu, Ying Nian Wu
2002	—	`conf`	Statistical Modeling of Texture Sketch. ECCV (3) Ying Nian Wu, Song Chun Zhu, Cheng-en Guo
2002	—	`conf`	What Are Textons? ECCV (4) Song Chun Zhu, Cheng-en Guo, Ying Nian Wu, Yizhou Wang
2001	—	`conf`	Dynamic Texture Recognition. CVPR (2) Payam Saisan, Gianfranco Doretto, Ying Nian Wu, Stefano Soatto
2001	A*	`conf`	Dynamic Textures. ICCV Stefano Soatto, Gianfranco Doretto, Ying Nian Wu
2001	J	`jnl`	Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help? Int. J. Comput. Vis. Alan L. Yuille, James M. Coughlan, Ying Nian Wu, Song Chun Zhu
2001	A*	`conf`	Visual Learning by Integrating Descriptive and Generative Methods. ICCV Cheng-en Guo, Song Chun Zhu, Ying Nian Wu
2000	J	`jnl`	Equivalence of Julesz Ensembles and FRAME Models. Int. J. Comput. Vis. Ying Nian Wu, Song Chun Zhu, Xiuwen Liu
2000	J	`jnl`	Exploring Texture Ensembles by Efficient Markov Chain Monte Carlo-Toward a 'Trichromacy' Theory of Texture. IEEE Trans. Pattern Anal. Mach. Intell. Song Chun Zhu, Xiuwen Liu, Ying Nian Wu
2000	A*	`conf`	Order Parameters for Minimax Entropy Distributions: When Does High Level Knowledge Help? CVPR Alan L. Yuille, James M. Coughlan, Song Chun Zhu, Ying Nian Wu
1999	A*	`conf`	Equivalence of Julesz and Gibbs Texture Ensembles. ICCV Ying Nian Wu, Song Chun Zhu, Xiuwen Liu
1999	J	`jnl`	From local features to global perception - A perspective of Gestalt psychology from Markov random field theory. Neurocomputing Song Chun Zhu, Ying Nian Wu
1998	J	`jnl`	Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling. Int. J. Comput. Vis. Song Chun Zhu, Ying Nian Wu, David Mumford
1997	J	`jnl`	Minimax Entropy Principle and Its Application to Texture Modeling. Neural Comput. Song Chun Zhu, Ying Nian Wu, David Mumford
1997	—	`conf`	Modeling images and textures by minimax entropy. Human Vision and Electronic Imaging Song-Chun Zhu, Ying Nian Wu, David Mumford
1996	A*	`conf`	FRAME: Filters, Random fields, and Minimax Entropy - Towards a Unified Theory for Texture Modeling. CVPR Song Chun Zhu, Ying Nian Wu, David Mumford