Tailin Wu - RankMe

76 papers A* 19A 2B 1Journal 52Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GenCP: Towards Generative Modeling Paradigm of Coupled Physics. CoRR Tianrun Gao, Haoren Zheng, Wenhao Deng, Haodong Feng, Tao Zhang, Ruiqi Feng, Qianyi Chen, Tailin Wu
2026	J	`jnl`	Neural Predictor-Corrector: Solving Homotopy Problems with Reinforcement Learning. CoRR Jiayao Mai, Bangyan Liao, Zhenjun Zhao, Yingping Zeng, Haoang Li, Javier Civera, Tailin Wu, Yi Zhou, Peidong Liu
2026	J	`jnl`	One step further with Monte-Carlo sampler to guide diffusion better. CoRR Minsi Ren, Wenhao Deng, Ruiqi Feng, Tailin Wu
2026	J	`jnl`	RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data. CoRR Peiyan Hu, Haodong Feng, Hongyuan Liu, Tongtong Yan, Wenhao Deng, Tianrun Gao, Rong Zheng, Haoren Zheng, Chenglei Yu, Chuanrui Wang, Kaiwen Li, Zhi-Ming Ma, Dezhi Zhou, Xingcai Lu, Dixia Fan, Tailin Wu
2026	J	`jnl`	Recurrent U-Net-based Graph Neural Network (RUGNN) for accurate deformation predictions in sheet material forming. Adv. Eng. Informatics Yingxue Zhao, Qianyi Chen, Haoran Li, Haosu Zhou, Hamid Reza Attar, Tobias Pfaff, Tailin Wu, Nan Li
2026	J	`jnl`	scDFM: Distributional Flow Matching Model for Robust Single-Cell Perturbation Prediction. CoRR Chenglei Yu, Chuanrui Wang, Bangyan Liao, Tailin Wu
2025	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Found. Trends Mach. Learn. Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2025	J	`jnl`	Beyond the Time Domain: Recent Advances on Frequency Transforms in Time Series Analysis. CoRR Qianru Zhang, Peng Yang, Honggang Wen, Xinzhu Li, Haixin Wang, Fang Sun, Zezheng Song, Zhichen Lai, Rui Ma, Ruihua Han, Tailin Wu, Siu-Ming Yiu, Yizhou Sun, Hongzhi Yin
2025	J	`jnl`	BuildArena: A Physics-Aligned Interactive Benchmark of LLMs for Engineering Construction. CoRR Tian Xia, Tianrun Gao, Wenhao Deng, Long Wei, Xiaowei Qian, Yixian Jiang, Chenglei Yu, Tailin Wu
2025	A*	`conf`	CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems. ICLR Long Wei, Haodong Feng, Yuchen Yang, Ruiqi Feng, Peiyan Hu, Xiang Zheng, Tao Zhang, Dixia Fan, Tailin Wu
2025	A*	`conf`	EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow. ICLR Yufei Huang, Yunshu Liu, Lirong Wu, Haitao Lin, Cheng Tan, Odin Zhang, Zhangyang Gao, Siyuan Li, Zicheng Liu, Yunfan Liu, Tailin Wu, Stan Z. Li
2025	J	`jnl`	EqCollide: Equivariant and Collision-Aware Deformable Objects Neural Simulator. CoRR Qianyi Chen, Tianrun Gao, Chenbo Jiang, Tailin Wu
2025	J	`jnl`	FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction. CoRR Qianru Zhang, Chenglei Yu, Haixin Wang, Yudong Yan, Yuansheng Cao, Siu-Ming Yiu, Tailin Wu, Hongzhi Yin
2025	J	`jnl`	FourierFlow: Frequency-aware Flow Matching for Generative Turbulence Modeling. CoRR Haixin Wang, Jiashu Pan, Hao Wu, Fan Zhang, Tailin Wu
2025	A*	`conf`	From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control. ICML Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2025	J	`jnl`	From Uncertain to Safe: Conformal Fine-Tuning of Diffusion Models for Safe PDE Control. CoRR Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2025	J	`jnl`	GGBall: Graph Generative Model on Poincaré Ball. CoRR Tianci Bu, Chuanrui Wang, Hao Ma, Haoren Zheng, Xin Lu, Tailin Wu
2025	J	`jnl`	Integrated AI and Communications: A Two-Way Catalysis Toward 6G and Beyond. J. Commun. Inf. Networks Xiang Cheng, Jianan Zhang, Ning Ding, Nan Li, Yong Li, Tailin Wu, Wei Xu, Jun Zhang, Qi Sun
2025	A*	`conf`	M2PDE: Compositional Generative Multiphysics and Multi-component PDE Simulation. ICML Tao Zhang, Zhenhai Liu, Feipeng Qi, Yongjun Jiao, Tailin Wu
2025	J	`jnl`	On the Design of One-step Diffusion via Shortcutting Flow Paths. CoRR Haitao Lin, Peiyan Hu, Minsi Ren, Zhifeng Gao, Zhi-Ming Ma, Guolin Ke, Tailin Wu, Stan Z. Li
2025	A*	`conf`	On the Guidance of Flow Matching. ICML Ruiqi Feng, Chenglei Yu, Wenhao Deng, Peiyan Hu, Tailin Wu
2025	J	`jnl`	On the Guidance of Flow Matching. CoRR Ruiqi Feng, Tailin Wu, Chenglei Yu, Wenhao Deng, Peiyan Hu
2025	A*	`conf`	Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model. ICLR Rundong He, Yicong Dong, Lanzhe Guo, Yilong Yin, Tailin Wu
2025	J	`jnl`	Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model. CoRR Rundong He, Yicong Dong, Lanzhe Guo, Yilong Yin, Tailin Wu
2025	J	`jnl`	Recurrent U-Net-Based Graph Neural Network (RUGNN) for Accurate Deformation Predictions in Sheet Material Forming. CoRR Yingxue Zhao, Qianyi Chen, Haoran Li, Haosu Zhou, Hamid Reza Attar, Tobias Pfaff, Tailin Wu, Nan Li
2025	A*	`conf`	Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization. AAAI Lirong Wu, Haitao Lin, Yufei Huang, Zhangyang Gao, Cheng Tan, Yunfan Liu, Tailin Wu, Stan Z. Li
2025	J	`jnl`	Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization. CoRR Lirong Wu, Haitao Lin, Yufei Huang, Zhangyang Gao, Cheng Tan, Yunfan Liu, Tailin Wu, Stan Z. Li
2025	J	`jnl`	T-SCEND: Test-time Scalable MCTS-enhanced Diffusion Model. CoRR Tao Zhang, Jia-Shu Pan, Ruiqi Feng, Tailin Wu
2025	J	`jnl`	Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration. CoRR Wenhao Deng, Long Wei, Chenglei Yu, Tailin Wu
2025	A*	`conf`	Wavelet Diffusion Neural Operator. ICLR Peiyan Hu, Rui Wang, Xiang Zheng, Tao Zhang, Haodong Feng, Ruiqi Feng, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2024	J	`jnl`	A Generative Approach to Control Complex Physical Systems. CoRR Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu
2024	J	`jnl`	A Moonshot for AI Oracles in the Sciences. CoRR Bryan E. Kaiser, Tailin Wu, Maike Sonnewald, Colin Thackray, Skylar Callis
2024	J	`jnl`	A Survey of Generative Techniques for Spatial-Temporal Data Mining. CoRR Qianru Zhang, Haixin Wang, Cheng Long, Liangcai Su, Xingwei He, Jianlong Chang, Tailin Wu, Hongzhi Yin, Siu-Ming Yiu, Qi Tian, Christian S. Jensen
2024	A*	`conf`	BENO: Boundary-embedded Neural Operators for Elliptic PDEs. ICLR Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu
2024	J	`jnl`	BENO: Boundary-embedded Neural Operators for Elliptic PDEs. CoRR Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu
2024	J	`jnl`	Closed-loop Diffusion Control of Complex Physical Systems. CoRR Long Wei, Haodong Feng, Peiyan Hu, Tao Zhang, Yuchen Yang, Xiang Zheng, Ruiqi Feng, Dixia Fan, Tailin Wu
2024	A*	`conf`	Compositional Generative Inverse Design. ICLR Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec
2024	J	`jnl`	Compositional Generative Inverse Design. CoRR Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec
2024	J	`jnl`	Compositional Generative Multiphysics and Multi-component Simulation. CoRR Tao Zhang, Zhenhai Liu, Feipeng Qi, Yongjun Jiao, Tailin Wu
2024	A*	`conf`	DiffPhyCon: A Generative Approach to Control Complex Physical Systems. NeurIPS Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu
2024	J	`jnl`	Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey. CoRR Haixin Wang, Yadi Cao, Zijie Huang, Yuxuan Liu, Peiyan Hu, Xiao Luo, Zezheng Song, Wanjia Zhao, Jilin Liu, Jinan Sun, Shikun Zhang, Long Wei, Yue Wang, Tailin Wu, Zhi-Ming Ma, Yizhou Sun
2024	A*	`conf`	Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution. AAAI Tailin Wu, Willie Neiswanger, Hongtao Zheng, Stefano Ermon, Jure Leskovec
2024	J	`jnl`	Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution. CoRR Tailin Wu, Willie Neiswanger, Hongtao Zheng, Stefano Ermon, Jure Leskovec
2024	J	`jnl`	Wavelet Diffusion Neural Operator. CoRR Peiyan Hu, Rui Wang, Xiang Zheng, Tao Zhang, Haodong Feng, Ruiqi Feng, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2023	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2023	J	`jnl`	How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation. CoRR Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Tailin Wu, Yilong Yin, Salman H. Khan, Lina Yao, Tongliang Liu, Kun Zhang
2023	A*	`conf`	Learning Controllable Adaptive Simulation for Multi-resolution Physics. ICLR Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec
2023	J	`jnl`	Learning Controllable Adaptive Simulation for Multi-resolution Physics. CoRR Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec
2023	—	`conf`	Robust X-ray Image Stitching Algorithm Based on Refining Matching Results of Feature Descriptors. ISBI Yefeng Liang, Shibo Li, Xingyu Li, Yucheng He, Ying Hu, Tailin Wu, Huiren Tao
2022	—	`conf`	An Automatic Scoliosis Diagnosis Platform Based on Deep Learning Approach. APIT Jinhang Li, Shibo Li, Zili Yang, Tailin Wu, Ying Hu
2022	A*	`conf`	Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator. KDD Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec
2022	J	`jnl`	Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator. CoRR Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec
2022	A*	`conf`	Learning to Accelerate Partial Differential Equations via Latent Global Evolution. NeurIPS Tailin Wu, Takashi Maruyama, Jure Leskovec
2022	J	`jnl`	Learning to Accelerate Partial Differential Equations via Latent Global Evolution. CoRR Tailin Wu, Takashi Maruyama, Jure Leskovec
2022	J	`jnl`	Toward a more accurate 3D atlas of C. elegans neurons. BMC Bioinform. Michael Skuhersky, Tailin Wu, Eviatar Yemini, Amin Nejatbakhsh, Edward S. Boyden, Max Tegmark
2022	J	`jnl`	ViRel: Unsupervised Visual Relations Discovery with Graph-level Analogy. CoRR Daniel Zeng, Tailin Wu, Jure Leskovec
2022	A*	`conf`	ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time. NeurIPS Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosic, Jure Leskovec
2022	J	`jnl`	ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time. CoRR Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosic, Jure Leskovec
2020	A*	`conf`	AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. NeurIPS Silviu-Marian Udrescu, Andrew K. Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
2020	J	`jnl`	AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. CoRR Silviu-Marian Udrescu, Andrew K. Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
2020	J	`jnl`	Discovering Nonlinear Relations with Minimum Predictive Information Regularization. CoRR Tailin Wu, Thomas M. Breuel, Michael Skuhersky, Jan Kautz
2020	A*	`conf`	Graph Information Bottleneck. NeurIPS Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec
2020	J	`jnl`	Graph Information Bottleneck. CoRR Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec
2020	J	`jnl`	Intelligence, physics and information - the tradeoff between accuracy and simplicity in machine learning. CoRR Tailin Wu
2020	B	`conf`	LBNN: Perceiving the State Changes of a Core Telecommunications Network via Linear Bayesian Neural Network. ICPADS Yanying Lin, Kejiang Ye, Ming Chen, Naitian Deng, Tailin Wu, Cheng-Zhong Xu
2020	J	`jnl`	Pareto-Optimal Data Compression for Binary Classification Tasks. Entropy Max Tegmark, Tailin Wu
2020	A*	`conf`	Phase Transitions for the Information Bottleneck in Representation Learning. ICLR Tailin Wu, Ian S. Fischer
2020	J	`jnl`	Phase Transitions for the Information Bottleneck in Representation Learning. CoRR Tailin Wu, Ian S. Fischer
2019	A	`conf`	Learnability for the Information Bottleneck. UAI Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
2019	J	`jnl`	Learnability for the Information Bottleneck. CoRR Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
2019	J	`jnl`	Learnability for the Information Bottleneck. Entropy Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
2019	J	`jnl`	Pareto-optimal data compression for binary classification tasks. CoRR Max Tegmark, Tailin Wu
2018	J	`jnl`	Meta-learning autoencoders for few-shot prediction. CoRR Tailin Wu, John Peurifoy, Isaac L. Chuang, Max Tegmark
2018	J	`jnl`	Toward an AI Physicist for Unsupervised Learning. CoRR Tailin Wu, Max Tegmark
2017	A	`conf`	Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels. UAI Curtis G. Northcutt, Tailin Wu, Isaac L. Chuang
2017	J	`jnl`	Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels. CoRR Curtis G. Northcutt, Tailin Wu, Isaac L. Chuang