Renjie Liao - RankMe

150 papers A* 33A 8B 3Misc 5Journal 79Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Point transformer for protein structural heterogeneity analysis using CryoEM. CoRR Muyuan Chen, Muchen Li, Renjie Liao
2026	J	`jnl`	Stable Velocity: A Variance Perspective on Flow Matching. CoRR Donglin Yang, Yongxing Zhang, Xin Yu, Liang Hou, Xin Tao, Pengfei Wan, Xiaojuan Qi, Renjie Liao
2026	J	`jnl`	TrajLoom: Dense Future Trajectory Generation from Video. CoRR Zewei Zhang, Jia Jun Cheng Xian, Kaiwen Liu, Ming Liang, Hang Chu, Jun Chen, Renjie Liao
2025	J	`jnl`	An Information-Theoretic Framework for Out-of-Distribution Generalization With Applications to Stochastic Gradient Langevin Dynamics. IEEE Trans. Inf. Theory Wenliang Liu, Guanding Yu, Lele Wang, Renjie Liao
2025	J	`jnl`	ControlEchoSynth: Boosting Ejection Fraction Estimation Models via Controlled Video Diffusion. CoRR Nima Kondori, Hanwen Liang, Hooman Vaseli, Bingyu Xie, Christina Luong, Purang Abolmaesumi, Teresa Tsang, Renjie Liao
2025	J	`jnl`	Free Lunch Alignment of Text-to-Image Diffusion Models without Preference Image Pairs. CoRR Jia Jun Cheng Xian, Muchen Li, Haotian Yang, Xin Tao, Pengfei Wan, Leonid Sigal, Renjie Liao
2025	J	`jnl`	Joint Generative Modeling of Grounded Scene Graphs and Images via Diffusion Models. Trans. Mach. Learn. Res. Bicheng Xu, Qi Yan, Renjie Liao, Lele Wang, Leonid Sigal
2025	A*	`conf`	LatentHOI: On the Generalizable Hand Object Motion Generation with Latent Hand Diffusion. CVPR Muchen Li, Sammy Christen, Chengde Wan, Yujun Cai, Renjie Liao, Leonid Sigal, Shugao Ma
2025	J	`jnl`	Learning Latent Part-Whole Hierarchies for Point Clouds. Int. J. Comput. Vis. Xiang Gao, Wei Hu, Renjie Liao
2025	—	`conf`	Leveraging MoE-Based Large Language Model for Zero-Shot Multi-Task Semantic Communication. ICC Sin-Yu Huang, Renjie Liao, Vincent W. S. Wong
2025	A*	`conf`	Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation. ICML Sadegh Mahdavi, Muchen Li, Kaiwen Liu, Christos Thrampoulidis, Leonid Sigal, Renjie Liao
2025	J	`jnl`	Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation. CoRR Sadegh Mahdavi, Muchen Li, Kaiwen Liu, Christos Thrampoulidis, Leonid Sigal, Renjie Liao
2025	A*	`conf`	MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation. CVPR Yuxiang Fu, Qi Yan, Lele Wang, Ke Li, Renjie Liao
2025	J	`jnl`	MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation. CoRR Yuxiang Fu, Qi Yan, Lele Wang, Ke Li, Renjie Liao
2025	J	`jnl`	Neural MJD: Neural Non-Stationary Merton Jump Diffusion for Time Series Prediction. CoRR Yuanpei Gao, Qi Yan, Yan Leng, Renjie Liao
2025	J	`jnl`	QDM: Quadtree-Based Region-Adaptive Sparse Diffusion Models for Efficient Image Super-Resolution. CoRR Donglin Yang, Paul Vicol, Xiaojuan Qi, Renjie Liao, Xiaofan Zhang
2025	J	`jnl`	RETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis. CoRR Robin Yadav, Qi Yan, Guy Wolf, Avishek Joey Bose, Renjie Liao
2025	J	`jnl`	Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection. CoRR Sadegh Mahdavi, Branislav Kisacanin, Shubham Toshniwal, Wei Du, Ivan Moshkov, George Armstrong, Renjie Liao, Christos Thrampoulidis, Igor Gitman
2025	J	`jnl`	Score Augmentation for Diffusion Models. CoRR Liang Hou, Yuan Gao, Boyuan Jiang, Xin Tao, Qi Yan, Renjie Liao, Pengfei Wan, Di Zhang, Kun Gai
2025	J	`jnl`	StreamSplat: Towards Online Dynamic 3D Reconstruction from Uncalibrated Video Streams. CoRR Zike Wu, Qi Yan, Xuanyu Yi, Lele Wang, Renjie Liao
2025	A*	`conf`	SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups. ICLR Yongxing Zhang, Donglin Yang, Renjie Liao
2025	—	`conf`	Test-Time Steering for Lossless Text Compression via Weighted Product of Experts. EMNLP (Findings) Qihang Zhang, Muchen Li, Ziao Wang, Renjie Liao, Lele Wang
2025	J	`jnl`	Test-Time Steering for Lossless Text Compression via Weighted Product of Experts. CoRR Qihang Zhang, Muchen Li, Ziao Wang, Renjie Liao, Lele Wang
2025	A	`conf`	TrajFlow: Multi-modal Motion Prediction via Flow Matching. IROS Qi Yan, Brian Zhang, Yutong Zhang, Daniel Yang, Joshua White, Di Chen, Jiachao Liu, Langechuan Liu, Binnan Zhuang, Shaoshuai Shi, Renjie Liao
2025	J	`jnl`	TrajFlow: Multi-modal Motion Prediction via Flow Matching. CoRR Qi Yan, Brian Zhang, Yutong Zhang, Daniel Yang, Joshua White, Di Chen, Jiachao Liu, Langechuan Liu, Binnan Zhuang, Shaoshuai Shi, Renjie Liao
2025	J	`jnl`	UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models. CoRR Guanlong Jiao, Biqing Huang, Kuan-Chieh Wang, Renjie Liao
2024	B	`conf`	An Information-Theoretic Framework for Out-of-Distribution Generalization. ISIT Wenliang Liu, Guanding Yu, Lele Wang, Renjie Liao
2024	J	`jnl`	An Information-Theoretic Framework for Out-of-Distribution Generalization. CoRR Wenliang Liu, Guanding Yu, Lele Wang, Renjie Liao
2024	J	`jnl`	From Graph Diffusion to Graph Classification. CoRR Jia Jun Cheng Xian, Sadegh Mahdavi, Renjie Liao, Oliver Schulte
2024	J	`jnl`	Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos. CoRR Jiahe Liu, Youran Qu, Qi Yan, Xiaohui Zeng, Lele Wang, Renjie Liao
2024	A*	`conf`	Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing. CVPR Bi'an Du, Xiang Gao, Wei Hu, Renjie Liao
2024	J	`jnl`	Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing. CoRR Bi'an Du, Xiang Gao, Wei Hu, Renjie Liao
2024	J	`jnl`	Joint Generative Modeling of Scene Graphs and Images via Diffusion Models. CoRR Bicheng Xu, Qi Yan, Renjie Liao, Lele Wang, Leonid Sigal
2024	A*	`conf`	Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders. ICML Xue Yu, Muchen Li, Yan Leng, Renjie Liao
2024	A*	`conf`	Memorization Capacity of Multi-Head Attention in Transformers. ICLR Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis
2024	J	`jnl`	Multi-scale Latent Point Consistency Models for 3D Shape Generation. CoRR Bi'an Du, Wei Hu, Renjie Liao
2024	—	`conf`	NTIRE 2024 Quality Assessment of AI-Generated Content Challenge. CVPR Workshops Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li, Tengchuan Kou, Wei Sun, Haoning Wu, Yixuan Gao, Yuqin Cao, Zicheng Zhang, Xiele Wu, Radu Timofte, Fei Peng, Huiyuan Fu, Anlong Ming, Chuanming Wang, Huadong Ma, Shuai He, Zifei Dou, Shu Chen, Huacong Zhang, Haiyi Xie, Chengwei Wang, Baoying Chen, Jishen Zeng, Jianquan Yang, Weigang Wang, Xi Fang, Xiaoxin Lv, Jun Yan, Tianwu Zhi, Yabin Zhang, Yaohui Li, Yang Li, Jingwen Xu, Jianzhao Liu, Yiting Liao, Junlin Li, Zihao Yu, Fengbin Guan, Yiting Lu, Xin Li, Hossein Motamednia, S. Farhad Hosseini-Benvidi, Ahmad Mahmoudi-Aznaveh, Azadeh Mansouri, Ganzorig Gankhuyag, Kihwan Yoon, Yifang Xu, Haotian Fan, Fangyuan Kong, Shiling Zhao, Weifeng Dong, Haibing Yin, Li Zhu, Zhiling Wang, Bingchen Huang, Avinab Saha, Sandeep Mishra, Shashank Gupta, Rajesh Sureddi, Oindrila Saha, Luigi Celona, Simone Bianco, Paolo Napoletano, Raimondo Schettini, Junfeng Yang, Jing Fu, Wei Zhang, Wenzhi Cao, Limei Liu, Han Peng, Weijun Yuan, Zhan Li, Yihang Cheng, Yifan Deng, Haohui Li, Bowen Qu, Yao Li, Shuqing Luo, Shunzhou Wang, Wei Gao, Zihao Lu, Marcos V. Conde, Xinrui Wang, Zhibo Chen, Ruling Liao, Yan Ye, Qiulin Wang, Bing Li, Zhaokun Zhou, Miao Geng, Rui Chen, Xin Tao, Xiaoyu Liang, Shangkun Sun, Xingyuan Ma, Jiaze Li, Mengduo Yang, Haoran Xu, Jie Zhou, Shiding Zhu, Bohan Yu, Pengfei Chen, Xinrui Xu, Jiabin Shen, Zhichao Duan, Erfan Asadi, Jiahe Liu, Qi Yan, Youran Qu, Xiaohui Zeng, Lele Wang, Renjie Liao
2024	Misc	`conf`	Revisiting the Equivalence of In-Context Learning and Gradient Descent: The Impact of Data Distribution. ICASSP Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis
2024	A	`conf`	Self-Supervised Relation Alignment for Scene Graph Generation. WACV Bicheng Xu, Renjie Liao, Leonid Sigal
2024	J	`jnl`	SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation. Trans. Mach. Learn. Res. Qi Yan, Zhengyang Liang, Yang Song, Renjie Liao, Lele Wang
2024	J	`jnl`	SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups. CoRR Yongxing Zhang, Donglin Yang, Renjie Liao
2023	—	`conf`	EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms. MICCAI (4) Masoud Mokhtari, Mobina Mahdavi, Hooman Vaseli, Christina Luong, Purang Abolmaesumi, Teresa S. M. Tsang, Renjie Liao
2023	J	`jnl`	EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms. CoRR Masoud Mokhtari, Mobina Mahdavi, Hooman Vaseli, Christina Luong, Purang Abolmaesumi, Teresa S. M. Tsang, Renjie Liao
2023	—	`conf`	GEMTrans: A General, Echocardiography-Based, Multi-level Transformer Framework for Cardiovascular Diagnosis. MLMI@MICCAI (2) Masoud Mokhtari, Neda Ahmadi, Teresa S. M. Tsang, Purang Abolmaesumi, Renjie Liao
2023	J	`jnl`	GEMTrans: A General, Echocardiography-based, Multi-Level Transformer Framework for Cardiovascular Diagnosis. CoRR Masoud Mokhtari, Neda Ahmadi, Teresa S. M. Tsang, Purang Abolmaesumi, Renjie Liao
2023	J	`jnl`	GraphPNAS: Learning Probabilistic Graph Generators for Neural Architecture Search. Trans. Mach. Learn. Res. Muchen Li, Jeffrey Yunfan Liu, Leonid Sigal, Renjie Liao
2023	J	`jnl`	Memorization Capacity of Multi-Head Attention in Transformers. CoRR Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis
2023	A	`conf`	NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds. WACV Weiwei Sun, Daniel Rebain, Renjie Liao, Vladimir Tankovich, Soroosh Yazdani, Kwang Moo Yi, Andrea Tagliasacchi
2023	A*	`conf`	Scaling Forward Gradient With Local Losses. ICLR Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton
2023	J	`jnl`	Self-Supervised Relation Alignment for Scene Graph Generation. CoRR Bicheng Xu, Renjie Liao, Leonid Sigal
2023	A*	`conf`	Specformer: Spectral Graph Neural Networks Meet Transformers. ICLR Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao
2023	J	`jnl`	Specformer: Spectral Graph Neural Networks Meet Transformers. CoRR Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao
2023	J	`jnl`	SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation. CoRR Qi Yan, Zhengyang Liang, Yang Song, Renjie Liao, Lele Wang
2023	J	`jnl`	Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks. Trans. Mach. Learn. Res. Sadegh Mahdavi, Kevin Swersky, Thomas Kipf, Milad Hashemi, Christos Thrampoulidis, Renjie Liao
2023	A	`conf`	VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge. WACV Sahithya Ravi, Aditya Chinchure, Leonid Sigal, Renjie Liao, Vered Shwartz
2022	—	`conf`	EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks. MICCAI (4) Masoud Mokhtari, Teresa Tsang, Purang Abolmaesumi, Renjie Liao
2022	J	`jnl`	EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks. CoRR Masoud Mokhtari, Teresa Tsang, Purang Abolmaesumi, Renjie Liao
2022	J	`jnl`	Gaussian-Bernoulli RBMs Without Tears. CoRR Renjie Liao, Simon Kornblith, Mengye Ren, David J. Fleet, Geoffrey E. Hinton
2022	J	`jnl`	GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. IEEE Trans. Pattern Anal. Mach. Intell. Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia
2022	J	`jnl`	GraphPNAS: Learning Distribution of Good Neural Architectures via Deep Graph Generative Models. CoRR Muchen Li, Jeffrey Yunfan Liu, Leonid Sigal, Renjie Liao
2022	J	`jnl`	Learning Latent Part-Whole Hierarchies for Point Clouds. CoRR Xiang Gao, Wei Hu, Renjie Liao
2022	J	`jnl`	NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds. CoRR Weiwei Sun, Daniel Rebain, Renjie Liao, Vladimir Tankovich, Soroosh Yazdani, Kwang Moo Yi, Andrea Tagliasacchi
2022	J	`jnl`	Scaling Forward Gradient With Local Losses. CoRR Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton
2022	J	`jnl`	Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks. CoRR Sadegh Mahdavi, Kevin Swersky, Thomas Kipf, Milad Hashemi, Christos Thrampoulidis, Renjie Liao
2022	J	`jnl`	VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge. CoRR Sahithya Ravi, Aditya Chinchure, Leonid Sigal, Renjie Liao, Vered Shwartz
2021	A*	`conf`	A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. ICLR Renjie Liao, Raquel Urtasun, Richard S. Zemel
2021	A*	`conf`	Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving. ICML Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon
2021	—	`—`	Deep Learning on Graphs: Theory, Models, Algorithms and Applications. Renjie Liao
2021	—	`conf`	Imitation Learning From Inconcurrent Multi-Agent Interactions. CDC Xin Zhang, Weixiao Huang, Yanhua Li, Renjie Liao, Ziming Zhang
2021	A	`conf`	LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. IROS Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun
2021	J	`jnl`	LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. CoRR Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun
2021	A*	`conf`	LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. ICCV Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, Raquel Urtasun
2021	J	`jnl`	LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. CoRR Alexander Cui, Abbas Sadat, Sergio Casas, Renjie Liao, Raquel Urtasun
2021	A	`conf`	NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation. UAI Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao
2021	J	`jnl`	NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation. CoRR Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao
2021	J	`jnl`	Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting. CoRR Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun
2021	A	`conf`	Safety-Oriented Pedestrian Occupancy Forecasting. IROS Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun
2021	J	`jnl`	Structure-Coherent Deep Feature Learning for Robust Face Alignment. IEEE Trans. Image Process. Chunze Lin, Beier Zhu, Quan Wang, Renjie Liao, Chen Qian, Jiwen Lu, Jie Zhou
2020	J	`jnl`	A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. CoRR Renjie Liao, Raquel Urtasun, Richard S. Zemel
2020	—	`conf`	DSDNet: Deep Structured Self-driving Network. ECCV (21) Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun
2020	J	`jnl`	DSDNet: Deep Structured self-Driving Network. CoRR Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun
2020	J	`jnl`	Fast and Accurate: Structure Coherence Component for Face Alignment. CoRR Beier Zhu, Chunze Lin, Quan Wang, Renjie Liao, Chen Qian
2020	J	`jnl`	GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. CoRR Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia
2020	—	`conf`	Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. ECCV (23) Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun
2020	J	`jnl`	Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. CoRR Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun
2020	A*	`conf`	Latent Variable Modelling with Hyperbolic Normalizing Flows. ICML Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton
2020	J	`jnl`	Latent Variable Modelling with Hyperbolic Normalizing Flows. CoRR Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton
2020	—	`conf`	Learning Lane Graph Representations for Motion Forecasting. ECCV (2) Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun
2020	J	`jnl`	Learning Lane Graph Representations for Motion Forecasting. CoRR Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun
2020	J	`jnl`	Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation. CoRR Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon
2020	A*	`conf`	SpAGNN: Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. ICRA Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun
2020	—	`conf`	Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. ECCV (26) Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun
2020	J	`jnl`	Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. CoRR Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun
2019	J	`jnl`	Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models. CoRR Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard S. Zemel, Shengyu Zhang
2019	A*	`conf`	DARNet: Deep Active Ray Network for Building Segmentation. CVPR Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun
2019	J	`jnl`	DARNet: Deep Active Ray Network for Building Segmentation. CoRR Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun
2019	A*	`conf`	DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. ICCV Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun
2019	J	`jnl`	DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. CoRR Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun
2019	J	`jnl`	Deformable Filter Convolution for Point Cloud Reasoning. CoRR Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun
2019	Misc	`conf`	Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. CoRL Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun
2019	J	`jnl`	Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. CoRR Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun
2019	A*	`conf`	Efficient Graph Generation with Graph Recurrent Attention Networks. NeurIPS Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel
2019	J	`jnl`	Efficient Graph Generation with Graph Recurrent Attention Networks. CoRR Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel
2019	A*	`conf`	Incremental Few-Shot Learning with Attention Attractor Networks. NeurIPS Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel
2019	Misc	`conf`	Inference in Probabilistic Graphical Models by Graph Neural Networks. ACSSC KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
2019	—	`conf`	LanczosNet: Multi-Scale Deep Graph Convolutional Networks. ICLR (Poster) Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel
2019	J	`jnl`	LanczosNet: Multi-Scale Deep Graph Convolutional Networks. CoRR Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel
2019	A*	`conf`	Lorentzian Distance Learning for Hyperbolic Representations. ICML Marc Teva Law, Renjie Liao, Jake Snell, Richard S. Zemel
2019	J	`jnl`	Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. CoRR Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun
2019	A*	`conf`	UPSNet: A Unified Panoptic Segmentation Network. CVPR Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun
2019	J	`jnl`	UPSNet: A Unified Panoptic Segmentation Network. CoRR Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun
2018	A*	`conf`	GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation. CVPR Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, Jiaya Jia
2018	—	`conf`	Graph Partition Neural Networks for Semi-Supervised Classification. ICLR (Workshop) Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel
2018	J	`jnl`	Graph Partition Neural Networks for Semi-Supervised Classification. CoRR Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel
2018	J	`jnl`	Incremental Few-Shot Learning with Attention Attractor Networks. CoRR Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel
2018	J	`jnl`	Inference in Probabilistic Graphical Models by Graph Neural Networks. CoRR KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
2018	—	`conf`	Inference in probabilistic graphical models by Graph Neural Networks. ICLR (Workshop) KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
2018	A*	`conf`	Learning Deep Structured Active Contours End-to-End. CVPR Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun
2018	J	`jnl`	Learning deep structured active contours end-to-end. CoRR Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun
2018	—	`conf`	Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. ICLR (Workshop) Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Raquel Urtasun, Richard S. Zemel
2018	—	`conf`	NerveNet: Learning Structured Policy with Graph Neural Networks. ICLR (Poster) Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler
2018	A*	`conf`	Neural Guided Constraint Logic Programming for Program Synthesis. NeurIPS Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel
2018	J	`jnl`	Neural Guided Constraint Logic Programming for Program Synthesis. CoRR Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel
2018	A*	`conf`	Reviving and Improving Recurrent Back-Propagation. ICML Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel
2018	J	`jnl`	Reviving and Improving Recurrent Back-Propagation. CoRR Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel
2018	—	`conf`	Understanding Short-Horizon Bias in Stochastic Meta-Optimization. ICLR (Poster) Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse
2018	J	`jnl`	Understanding Short-Horizon Bias in Stochastic Meta-Optimization. CoRR Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse
2017	A*	`conf`	3D Graph Neural Networks for RGBD Semantic Segmentation. ICCV Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun
2017	A*	`conf`	Detail-Revealing Deep Video Super-Resolution. ICCV Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia
2017	J	`jnl`	Detail-revealing Deep Video Super-resolution. CoRR Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia
2017	B	`conf`	Learning to generate images with perceptual similarity metrics. ICIP Jake Snell, Karl Ridgeway, Renjie Liao, Brett D. Roads, Michael C. Mozer, Richard S. Zemel
2017	—	`conf`	Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. ICLR (Poster) Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel
2017	A*	`conf`	Situation Recognition with Graph Neural Networks. ICCV Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler
2017	J	`jnl`	Situation Recognition with Graph Neural Networks. CoRR Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler
2016	—	`conf`	Learning Deep Parsimonious Representations. NIPS Renjie Liao, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun
2016	J	`jnl`	Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. CoRR Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel
2015	J	`jnl`	Bounded-Distortion Metric Learning. CoRR Renjie Liao, Jianping Shi, Ziyang Ma, Jun Zhu, Jiaya Jia
2015	A*	`conf`	Deep Edge-Aware Filters. ICML Li Xu, Jimmy S. J. Ren, Qiong Yan, Renjie Liao, Jiaya Jia
2015	A*	`conf`	Handling motion blur in multi-frame super-resolution. CVPR Ziyang Ma, Renjie Liao, Xin Tao, Li Xu, Jiaya Jia, Enhua Wu
2015	J	`jnl`	Personal object discovery in first-person videos. IEEE Trans. Image Process. Cewu Lu, Renjie Liao, Jiaya Jia
2015	A*	`conf`	Semantic Segmentation with Object Clique Potential. ICCV Xiaojuan Qi, Jianping Shi, Shu Liu, Renjie Liao, Jiaya Jia
2015	A*	`conf`	Video Super-Resolution via Deep Draft-Ensemble Learning. ICCV Renjie Liao, Xin Tao, Ruiyu Li, Ziyang Ma, Jiaya Jia
2014	B	`conf`	A confidence growing model for super-resolution. ICIP Sina Lin, Zengchang Qin, Renjie Liao, Tao Wan
2014	A*	`conf`	Learning Important Spatial Pooling Regions for Scene Classification. CVPR Di Lin, Cewu Lu, Renjie Liao, Jiaya Jia
2014	A	`conf`	Nonparametric bayesian upstream supervised multi-modal topic models. WSDM Renjie Liao, Jun Zhu, Zengchang Qin
2013	Misc	`conf`	A robust fusion scheme for multifocus images using sparse features. ICASSP Tao Wan, Zengchang Qin, Chenchen Zhu, Renjie Liao
2013	A*	`conf`	CoDeL: A Human Co-detection and Labeling Framework. ICCV Jianping Shi, Renjie Liao, Jiaya Jia
2012	—	`conf`	Image Super-Resolution Using Local Learnable Kernel Regression. ACCV (3) Renjie Liao, Zengchang Qin
2010	Misc	`conf`	A novel serial crime prediction model based on Bayesian learning theory. ICMLC Renjie Liao, Xueyao Wang, Lun Li, Zengchang Qin
2010	—	`conf`	Improved Quantum Particle Swarm Optimization by Bloch Sphere. ICSI (1) Yu Du, Haibin Duan, Renjie Liao, Xihua Li