Wu, Tailin

30 publications

FnTML 2025 Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems 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

ICLR 2025 CL-DiffPhyCon: Closed-Loop Diffusion Control of Complex Physical Systems Long Wei, Haodong Feng, Yuchen Yang, Ruiqi Feng, Peiyan Hu, Xiang Zheng, Tao Zhang, Dixia Fan, Tailin Wu

ICLR 2025 EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow 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

ICML 2025 From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu

ICML 2025 M2PDE: Compositional Generative Multiphysics and Multi-Component PDE Simulation Tao Zhang, Zhenhai Liu, Feipeng Qi, Yongjun Jiao, Tailin Wu

ICML 2025 On the Guidance of Flow Matching Ruiqi Feng, Chenglei Yu, Wenhao Deng, Peiyan Hu, Tailin Wu

ICLR 2025 Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model Rundong He, Yicong Dong, Lan-Zhe Guo, Yilong Yin, Tailin Wu

AAAI 2025 Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization Lirong Wu, Haitao Lin, Yufei Huang, Zhangyang Gao, Cheng Tan, Yunfan Liu, Tailin Wu, Stan Z. Li

ICLR 2025 Wavelet Diffusion Neural Operator Peiyan Hu, Rui Wang, Xiang Zheng, Tao Zhang, Haodong Feng, Ruiqi Feng, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu

NeurIPSW 2024 A Probabilistic Generative Method for Safe Physical System Control Problems Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu

ICLR 2024 BENO: Boundary-Embedded Neural Operators for Elliptic PDEs Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu

ICLR 2024 Compositional Generative Inverse Design Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec

NeurIPS 2024 DiffPhyCon: A Generative Approach to Control Complex Physical Systems Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu

ICLRW 2024 Generative PDE Control Long Wei, Peiyan Hu, Ruiqi Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu

ICLRW 2024 How Well Does GPT-4V(ision) Adapt to Distribution Shifts? a Preliminary Investigation Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Tailin Wu, Yilong Yin, Salman Khan, Lina Yao, Tongliang Liu, Kun Zhang

AAAI 2024 Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution Tailin Wu, Willie Neiswanger, Hongtao Zheng, Stefano Ermon, Jure Leskovec

ICLRW 2024 Xddpm: Explainable Denoising Diffusion Prob- Abilistic Model for Scientific Modeling Qianru Zhang, Chenglei Yu, Yudong Yan, Xiangyu Kuang, Yi Ma, Yuansheng Cao, Siu Ming Yiu, Tailin Wu

NeurIPSW 2023 BENO: Boundary-Embedded Neural Operators for Elliptic PDEs Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu

NeurIPSW 2023 Compositional Generative Inverse Design Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec

ICLR 2023 Learning Controllable Adaptive Simulation for Multi-Resolution Physics Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec

NeurIPSW 2022 Learning Controllable Adaptive Simulation for Multi-Scale Physics Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec

NeurIPSW 2022 Learning Efficient Hybrid Particle-Continuum Representations of Non-Equilibrium N-Body Systems Tailin Wu, Michael Sun, H.G. Jason Chou, Pranay Reddy Samala, Sithipont Cholsaipant, Sophia Kivelson, Jacqueline Yau, Zhitao Ying, E. Paulo Alves, Jure Leskovec, Frederico Fiuza

NeurIPS 2022 Learning to Accelerate Partial Differential Equations via Latent Global Evolution Tailin Wu, Takashi Maruyama, Jure Leskovec

NeurIPS 2022 ZeroC: A Neuro-Symbolic Model for Zero-Shot Concept Recognition and Acquisition at Inference Time Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosic, Jure Leskovec

NeurIPS 2020 AI Feynman 2.0: Pareto-Optimal Symbolic Regression Exploiting Graph Modularity Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark

NeurIPS 2020 Graph Information Bottleneck Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec

ICLR 2020 Phase Transitions for the Information Bottleneck in Representation Learning Tailin Wu, Ian Fischer

UAI 2019 Learnability for the Information Bottleneck Tailin Wu, Ian Fischer, Isaac L. Chuang, Max Tegmark

ICLRW 2019 Learnability for the Information Bottleneck Tailin Wu, Ian Fischer, Isaac Chuang, Max Tegmark

UAI 2017 Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels Curtis G. Northcutt, Tailin Wu, Isaac L. Chuang