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2020 – today
- 2024
[c23]Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec:
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs. ICLR 2024- [c22]Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui:
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing. ICLR 2024 - [c21]Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui:
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs. ICML 2024 - [c20]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML 2024 - [i32]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR abs/2401.11037 (2024) - [i31]Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui:
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs. CoRR abs/2401.11708 (2024) - [i30]Xinchen Zhang, Ling Yang, Yaqi Cai, Zhaochen Yu, Jiake Xie, Ye Tian, Minkai Xu, Yong Tang, Yujiu Yang, Bin Cui:
RealCompo: Dynamic Equilibrium between Realism and Compositionality Improves Text-to-Image Diffusion Models. CoRR abs/2402.12908 (2024) - [i29]Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui:
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing. CoRR abs/2402.16627 (2024) - [i28]Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin Cui:
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models. CoRR abs/2406.04271 (2024) - [i27]Siyi Gu, Minkai Xu, Alexander S. Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon:
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. CoRR abs/2407.01648 (2024) - [i26]Ling Yang, Zixiang Zhang, Zhilong Zhang, Xingchao Liu, Minkai Xu, Wentao Zhang, Chenlin Meng, Stefano Ermon, Bin Cui:
Consistency Flow Matching: Defining Straight Flows with Velocity Consistency. CoRR abs/2407.02398 (2024) - [i25]Sitao Luan, Chenqing Hua, Qincheng Lu, Liheng Ma, Lirong Wu, Xinyu Wang, Minkai Xu, Xiao-Wen Chang, Doina Precup, Rex Ying, Stan Z. Li, Jian Tang, Guy Wolf, Stefanie Jegelka:
The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. CoRR abs/2407.09618 (2024) - [i24]Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Zou, Stefano Ermon:
TFG: Unified Training-Free Guidance for Diffusion Models. CoRR abs/2409.15761 (2024) - [i23]Bohan Zeng, Ling Yang, Siyu Li, Jiaming Liu, Zixiang Zhang, Juanxi Tian, Kaixin Zhu, Yongzhen Guo, Fu-Yun Wang, Minkai Xu, Stefano Ermon, Wentao Zhang:
Trans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis. CoRR abs/2410.07155 (2024) - 2023
- [c19]Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Rex Ying, Jian Tang, Peilin Zhao, Dinghao Wu:
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning. ICML 2023: 22028-22041 - [c18]Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong, Bowen Gao, Hao Zhou, Wei-Ying Ma, Yanyan Lan:
Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D. ICML 2023: 28277-28299 - [c17]Minkai Xu, Alexander S. Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec:
Geometric Latent Diffusion Models for 3D Molecule Generation. ICML 2023: 38592-38610 - [c16]Minkai Xu
, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon:
Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834 - [c15]Chenqing Hua, Sitao Luan, Minkai Xu, Zhitao Ying, Jie Fu, Stefano Ermon, Doina Precup:
MUDiff: Unified Diffusion for Complete Molecule Generation. LoG 2023: 33 - [c14]Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon:
Scaling Riemannian Diffusion Models. NeurIPS 2023 - [c13]Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability. NeurIPS 2023 - [c12]Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma:
Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation. NeurIPS 2023 - [i22]Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability. CoRR abs/2304.14274 (2023) - [i21]Chenqing Hua, Sitao Luan, Minkai Xu, Rex Ying, Jie Fu, Stefano Ermon, Doina Precup:
MUDiff: Unified Diffusion for Complete Molecule Generation. CoRR abs/2304.14621 (2023) - [i20]Minkai Xu, Alexander S. Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec:
Geometric Latent Diffusion Models for 3D Molecule Generation. CoRR abs/2305.01140 (2023) - [i19]Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong, Bowen Gao, Hao Zhou, Wei-Ying Ma, Yanyan Lan:
Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D. CoRR abs/2305.13266 (2023) - [i18]Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang:
MADiff: Offline Multi-agent Learning with Diffusion Models. CoRR abs/2305.17330 (2023) - [i17]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:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i16]Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec:
VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs. CoRR abs/2308.02117 (2023) - [i15]Aaron Lou, Minkai Xu, Stefano Ermon:
Scaling Riemannian Diffusion Models. CoRR abs/2310.20030 (2023) - [i14]Yiming Wang, Yuxuan Song, Minkai Xu, Rui Wang, Hao Zhou, Weiying Ma:
RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation. CoRR abs/2311.14077 (2023) - [i13]Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma:
Equivariant Flow Matching with Hybrid Probability Transport. CoRR abs/2312.07168 (2023) - 2022
- [c11]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. ICLR 2022 - [c10]Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli:
Generative Coarse-Graining of Molecular Conformations. ICML 2022: 23213-23236 - [i12]Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli:
Generative Coarse-Graining of Molecular Conformations. CoRR abs/2201.12176 (2022) - [i11]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation. CoRR abs/2203.02923 (2022) - 2021
- [c9]Minkai Xu:
Towards Generalized Implementation of Wasserstein Distance in GANs. AAAI 2021: 10514-10522 - [c8]Minghuan Liu, Tairan He, Minkai Xu, Weinan Zhang:
Energy-Based Imitation Learning. AAMAS 2021: 809-817 - [c7]Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang:
Learning Neural Generative Dynamics for Molecular Conformation Generation. ICLR 2021 - [c6]Chence Shi, Shitong Luo, Minkai Xu, Jian Tang:
Learning Gradient Fields for Molecular Conformation Generation. ICML 2021: 9558-9568 - [c5]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. ICML 2021: 11537-11547 - [c4]Shitong Luo, Chence Shi, Minkai Xu, Jian Tang:
Predicting Molecular Conformation via Dynamic Graph Score Matching. NeurIPS 2021: 19784-19795 - [i10]Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang:
Learning Neural Generative Dynamics for Molecular Conformation Generation. CoRR abs/2102.10240 (2021) - [i9]Chence Shi, Shitong Luo, Minkai Xu, Jian Tang:
Learning Gradient Fields for Molecular Conformation Generation. CoRR abs/2105.03902 (2021) - [i8]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. CoRR abs/2105.07246 (2021) - 2020
- [c3]Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu:
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip. AAAI 2020: 5834-5841 - [c2]Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang:
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. ICLR 2020 - [c1]Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang:
A Graph to Graphs Framework for Retrosynthesis Prediction. ICML 2020: 8818-8827 - [i7]Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang:
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. CoRR abs/2001.09382 (2020) - [i6]Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang:
A Graph to Graphs Framework for Retrosynthesis Prediction. CoRR abs/2003.12725 (2020) - [i5]Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu:
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip. CoRR abs/2004.01454 (2020) - [i4]Yuxuan Song, Qiwei Ye, Minkai Xu, Tie-Yan Liu:
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator. CoRR abs/2004.01704 (2020) - [i3]Minghuan Liu, Tairan He, Minkai Xu, Weinan Zhang:
Energy-Based Imitation Learning. CoRR abs/2004.09395 (2020) - [i2]Minkai Xu, Mingxuan Wang, Zhouhan Lin, Hao Zhou, Weinan Zhang, Lei Li:
Reciprocal Supervised Learning Improves Neural Machine Translation. CoRR abs/2012.02975 (2020) - [i1]Minkai Xu, Zhiming Zhou, Guansong Lu, Jian Tang, Weinan Zhang, Yong Yu:
Sobolev Wasserstein GAN. CoRR abs/2012.03420 (2020)
Coauthor Index
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