Xu, Minkai

40 publications

AISTATS 2025 $f$-PO: Generalizing Preference Optimization with $f$-Divergence Minimization Jiaqi Han, Mingjian Jiang, Yuxuan Song, Stefano Ermon, Minkai Xu
NeurIPS 2025 3D Interaction Geometric Pre-Training for Molecular Relational Learning Namkyeong Lee, Yunhak Oh, Heewoong Noh, Gyoung S. Na, Minkai Xu, Hanchen, Tianfan Fu, Chanyoung Park
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
ICCV 2025 CHORDS: Diffusion Sampling Accelerator with Multi-Core Hierarchical ODE Solvers Jiaqi Han, Haotian Ye, Puheng Li, Minkai Xu, James Zou, Stefano Ermon
ICLR 2025 Energy-Based Diffusion Language Models for Text Generation Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat
AISTATS 2025 RetroDiff: Retrosynthesis as Multi-Stage Distribution Interpolation Yiming Wang, Yuxuan Song, Yiqun Wang, Minkai Xu, Rui Wang, Hao Zhou, Wei-Ying Ma
ICML 2025 Smooth Interpolation for Improved Discrete Graph Generative Models Yuxuan Song, Juntong Shi, Jingjing Gong, Minkai Xu, Stefano Ermon, Hao Zhou, Wei-Ying Ma
ICLR 2025 SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction Ling Yang, Zhaochen Yu, Tianjun Zhang, Minkai Xu, Joseph E. Gonzalez, Bin Cui, Shuicheng Yan
ICLR 2025 TabDiff: A Mixed-Type Diffusion Model for Tabular Data Generation Juntong Shi, Minkai Xu, Harper Hua, Hengrui Zhang, Stefano Ermon, Jure Leskovec
NeurIPS 2024 Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization Siyi Gu, Minkai Xu, Alexander Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon
NeurIPS 2024 Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin Cui
ICLR 2024 Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui
ICMLW 2024 Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design Aksh Garg, Jiaqi Han, Sanjay Nagaraj, Minkai Xu
ICMLW 2024 Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design Sanjay Nagaraj, Jiaqi Han, Aksh Garg, Minkai Xu
ICMLW 2024 Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design Jiaqi Han, Aksh Garg, Sanjay Nagaraj, Minkai Xu
ICML 2024 Equivariant Graph Neural Operator for Modeling 3D Dynamics Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
NeurIPS 2024 Geometric Trajectory Diffusion Models Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon
NeurIPS 2024 MADiff: Offline Multi-Agent Learning with Diffusion Models Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang
ICML 2024 Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui
NeurIPS 2024 RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models Xinchen Zhang, Ling Yang, Yaqi Cai, Zhaochen Yu, Kai-Ni Wang, Jiake Xie, Ye Tian, Minkai Xu, Yong Tang, Yujiu Yang, Bin Cui
NeurIPS 2024 TFG: Unified Training-Free Guidance for Diffusion Models Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Zou, Stefano Ermon
NeurIPSW 2024 TabDiff: A Unified Diffusion Model for Multi-Modal Tabular Data Generation Juntong Shi, Minkai Xu, Harper Hua, Hengrui Zhang, Stefano Ermon, Jure Leskovec
ICLR 2024 VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec
ICML 2023 Coarse-to-Fine: A Hierarchical Diffusion Model for Molecule Generation in 3D Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong, Bowen Gao, Hao Zhou, Wei-Ying Ma, Yanyan Lan
NeurIPS 2023 Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma
ICML 2023 FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Rex Ying, Jian Tang, Peilin Zhao, Dinghao Wu
ICML 2023 Geometric Latent Diffusion Models for 3D Molecule Generation Minkai Xu, Alexander S Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec
LoG 2023 MUDiff: Unified Diffusion for Complete Molecule Generation Chenqing Hua, Sitao Luan, Minkai Xu, Zhitao Ying, Jie Fu, Stefano Ermon, Doina Precup
NeurIPS 2023 Scaling Riemannian Diffusion Models Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon
NeurIPS 2023 When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup
ICML 2022 Generative Coarse-Graining of Molecular Conformations Wujie Wang, Minkai Xu, Chen Cai, Benjamin K Miller, Tess Smidt, Yusu Wang, Jian Tang, Rafael Gomez-Bombarelli
ICLR 2022 GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
ICML 2021 An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gomez-Bombarelli, Jian Tang
ICML 2021 Learning Gradient Fields for Molecular Conformation Generation Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
ICLR 2021 Learning Neural Generative Dynamics for Molecular Conformation Generation Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
NeurIPS 2021 Predicting Molecular Conformation via Dynamic Graph Score Matching Shitong Luo, Chence Shi, Minkai Xu, Jian Tang
AAAI 2021 Towards Generalized Implementation of Wasserstein Distance in GANs Minkai Xu
ICML 2020 A Graph to Graphs Framework for Retrosynthesis Prediction Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang
ICLR 2020 GraphAF: A Flow-Based Autoregressive Model for Molecular Graph Generation Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang
AAAI 2020 Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu