Jian Tang

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 170

Top Venues

Publications

Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled. Trans. Mach. Learn. Res. 2024 (2024)
Jianan Zhao, Hesham Mostafa, Mikhail Galkin, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang
GraphAny: A Foundation Model for Node Classification on Any Graph. CoRR (2024)
Haitao Mao, Jianan Zhao, Xiaoxin He, Zhikai Chen, Qian Huang, Zhaocheng Zhu, Jian Tang, Michael M. Bronstein, Xavier Bresson, Bryan Hooi, Haiyang Zhang, Xianfeng Tang, Luo Chen, Jiliang Tang
The 1st International Workshop on Graph Foundation Models (GFM). WWW (Companion Volume) (2024)
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
Towards Foundation Models for Knowledge Graph Reasoning. ICLR (2024)
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR (2024)
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation. CoRR (2024)
Jiarui Lu, Bozitao Zhong, Zuobai Zhang, Jian Tang
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling. ICLR (2024)
Jiarui Lu, Zuobai Zhang, Bozitao Zhong, Chence Shi, Jian Tang
Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations. CoRR (2024)
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 (2024)
Mikhail Galkin, Jincheng Zhou, Bruno F. Ribeiro, Jian Tang, Zhaocheng Zhu
Zero-shot Logical Query Reasoning on any Knowledge Graph. CoRR (2024)
Wentao Zhang, Guochen Yan, Yu Shen, Yang Ling, Yangyu Tao, Bin Cui, Jian Tang
NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention. SIGMOD Conference Companion (2024)
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Structure-Informed Protein Language Model. CoRR (2024)
Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled. CoRR (2024)
Arian R. Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom L. Blundell
Evaluating representation learning on the protein structure universe. CoRR (2024)
Arian Rokkum Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom L. Blundell
Evaluating Representation Learning on the Protein Structure Universe. ICLR (2024)
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
Towards Foundation Models for Knowledge Graph Reasoning. CoRR (2023)
Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Animashree Anandkumar
Multi-modal molecule structure-text model for text-based retrieval and editing. Nat. Mac. Intell. 5 (12) (2023)
Chuanrui Wang, Bozitao Zhong, Zuobai Zhang, Narendra Chaudhary, Sanchit Misra, Jian Tang
PDB-Struct: A Comprehensive Benchmark for Structure-based Protein Design. CoRR (2023)
Yangtian Zhang, Zuobai Zhang, Bozitao Zhong, Sanchit Misra, Jian Tang
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing. CoRR (2023)
Yangtian Zhang, Huiyu Cai, Chence Shi, Jian Tang
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking. ICLR (2023)
Zuobai Zhang, Minghao Xu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Enhancing Protein Language Models with Structure-based Encoder and Pre-training. CoRR (2023)
Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, Jian Tang
Protein Sequence and Structure Co-Design with Equivariant Translation. ICLR (2023)
Andreea Deac, Jian Tang
Evolving Computation Graphs. CoRR (2023)
Zhaocheng Zhu, Yuan Xue, Xinyun Chen, Denny Zhou, Jian Tang, Dale Schuurmans, Hanjun Dai
Large Language Models can Learn Rules. CoRR (2023)
Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang
GraphText: Graph Reasoning in Text Space. CoRR (2023)
Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik
Scientific discovery in the age of artificial intelligence. Nat. 620 (7972) (2023)
Fang Sun, Zhihao Zhan, Hongyu Guo, Ming Zhang, Jian Tang
GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow. CoRR (2023)
Cheng Yang, Hao Wang, Jian Tang, Chuan Shi, Maosong Sun, Ganqu Cui, Zhiyuan Liu
Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks. IEEE Trans. Neural Networks Learn. Syst. 34 (5) (2023)
Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël
Flaky Performances When Pretraining on Relational Databases (Student Abstract). AAAI (2023)
Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhiming Ma, Omar Yaghi, Anima Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. CoRR (2023)
Minghao Xu, Xinyu Yuan, Santiago Miret, Jian Tang
ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts. CoRR (2023)
Shengchao Liu, weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. NeurIPS (2023)
Shengchao Liu, Weitao Du, Zhiming Ma, Hongyu Guo, Jian Tang
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. CoRR (2023)
Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang
A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs. NeurIPS (2023)
Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. ICML (2023)
Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang
Learning on Large-scale Text-attributed Graphs via Variational Inference. ICLR (2023)
Jiarui Lu, Bozitao Zhong, Jian Tang
Score-based Enhanced Sampling for Protein Molecular Dynamics. CoRR (2023)
Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Protein Representation Learning by Geometric Structure Pretraining. ICLR (2023)
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR (2023)
Yangtian Zhang, Zuobai Zhang, Bozitao Zhong, Sanchit Misra, Jian Tang
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing. NeurIPS (2023)
Shengchao Liu, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Anthony Gitter, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar
A Text-guided Protein Design Framework. CoRR (2023)
Shengchao Liu, Hongyu Guo, Jian Tang
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching. ICLR (2023)
Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction. CoRR (2023)
Yu Li, Meng Qu, Jian Tang, Yi Chang
Signed Laplacian Graph Neural Networks. AAAI (2023)
Minghao Xu, Xinyu Yuan, Santiago Miret, Jian Tang
ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts. ICML (2023)
Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction. NeurIPS (2023)
Zhaocheng Zhu, Xinyu Yuan, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang
Learning to Efficiently Propagate for Reasoning on Knowledge Graphs. CoRR (2022)
Meng Qu, Huiyu Cai, Jian Tang
Neural Structured Prediction for Inductive Node Classification. ICLR (2022)
Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang
Structured Multi-task Learning for Molecular Property Prediction. CoRR (2022)
Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang
Neural-Symbolic Models for Logical Queries on Knowledge Graphs. CoRR (2022)
Mikhail Galkin, Zhaocheng Zhu, Hongyu Ren, Jian Tang
Inductive Logical Query Answering in Knowledge Graphs. CoRR (2022)
Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang
Structured Multi-task Learning for Molecular Property Prediction. AISTATS (2022)
Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Anima Anandkumar
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing. CoRR (2022)
Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Chang Ma, Runcheng Liu, Jian Tang
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding. NeurIPS (2022)
Meng Qu, Huiyu Cai, Jian Tang
Neural Structured Prediction for Inductive Node Classification. CoRR (2022)
Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt J. Kusner, Joan Lasenby, Qi Liu
Evaluating Self-Supervised Learning for Molecular Graph Embeddings. CoRR (2022)
Jing Zhang, Xiaokang Zhang, Jifan Yu, Jian Tang, Jie Tang, Cuiping Li, Hong Chen
Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering. ACL (1) (2022)
Shengchao Liu, Hongyu Guo, Jian Tang
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching. CoRR (2022)
Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang
Learning on Large-scale Text-attributed Graphs via Variational Inference. CoRR (2022)
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Bin Yang, Jian Tang, Christian S. Jensen
Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning. ICDE (2022)
Dingmin Wang, Shengchao Liu, Hanchen Wang, Linfeng Song, Jian Tang, Song Le, Bernardo Cuenca Grau, Qi Liu
Augmenting Message Passing by Retrieving Similar Graphs. CoRR (2022)
Minghao Xu, Yuanfan Guo, Xuanyu Zhu, Jiawen Li, Zhenbang Sun, Jian Tang, Yi Xu, Bingbing Ni
HIRL: A General Framework for Hierarchical Image Representation Learning. CoRR (2022)
Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, Jian Tang
Protein Sequence and Structure Co-Design with Equivariant Translation. CoRR (2022)
Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data. CoRR (2022)
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. ICLR (2022)
Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël
Flaky Performances when Pretraining on Relational Databases. CoRR (2022)
Michael Galkin, Zhaocheng Zhu, Hongyu Ren, Jian Tang
Inductive Logical Query Answering in Knowledge Graphs. NeurIPS (2022)
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation. CoRR (2022)
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)
Yangtian Zhang, Huiyu Cai, Chence Shi, Bozitao Zhong, Jian Tang
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking. CoRR (2022)
Zhaocheng Zhu, Chence Shi, Zuobai Zhang, Shengchao Liu, Minghao Xu, Xinyu Yuan, Yangtian Zhang, Junkun Chen, Huiyu Cai, Jiarui Lu, Chang Ma, Runcheng Liu, Louis-Pascal A. C. Xhonneux, Meng Qu, Jian Tang
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery. CoRR (2022)
Songtao Liu, Rex Ying, Zuobai Zhang, Peilin Zhao, Jian Tang, Lu Lin, Dinghao Wu
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree. CoRR (2022)
Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli
Generative Coarse-Graining of Molecular Conformations. CoRR (2022)
Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Chang Ma, Runcheng Liu, Jian Tang
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding. CoRR (2022)
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Bin Yang, Jian Tang, Christian S. Jensen
Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version. CoRR (2022)
Zuobai Zhang, Minghao Xu, Arian R. Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Protein Representation Learning by Geometric Structure Pretraining. CoRR (2022)
Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang
Neural-Symbolic Models for Logical Queries on Knowledge Graphs. ICML (2022)
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal A. C. Xhonneux, Jian Tang
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction. CoRR (2021)
Shitong Luo, Chence Shi, Minkai Xu, Jian Tang
Predicting Molecular Conformation via Dynamic Graph Score Matching. NeurIPS (2021)
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David Buckeridge, Gaétan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
Predicting Infectiousness for Proactive Contact Tracing. ICLR (2021)
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang
Unsupervised Path Representation Learning with Curriculum Negative Sampling. IJCAI (2021)
Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic
Neural Algorithmic Reasoners are Implicit Planners. CoRR (2021)
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)
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
Learning Gradient Fields for Molecular Conformation Generation. ICML (2021)
Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
GraphMix: Improved Training of GNNs for Semi-Supervised Learning. AAAI (2021)
Hangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang, Hongyu Guo
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction. ICML (2021)
Jian Tang, Fei Wang, Feixiong Cheng
Artificial Intelligence for Drug Discovery. KDD (2021)
Louis-Pascal A. C. Xhonneux, Andreea Deac, Petar Velickovic, Jian Tang
How to transfer algorithmic reasoning knowledge to learn new algorithms? NeurIPS (2021)
Minghao Xu, Meng Qu, Bingbing Ni, Jian Tang
Joint Modeling of Visual Objects and Relations for Scene Graph Generation. NeurIPS (2021)
Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic
Neural Algorithmic Reasoners are Implicit Planners. NeurIPS (2021)
Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
Learning Neural Generative Dynamics for Molecular Conformation Generation. CoRR (2021)
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhengyan Zhang, Zhiyuan Liu, Juanzi Li, Jian Tang
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation. Trans. Assoc. Comput. Linguistics 9 (2021)
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal A. C. Xhonneux, Jian Tang
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction. NeurIPS (2021)
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 (2021)
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang
Unsupervised Path Representation Learning with Curriculum Negative Sampling. CoRR (2021)
Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King
Utilizing graph machine learning within drug discovery and development. Briefings Bioinform. 22 (6) (2021)
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
Learning Gradient Fields for Molecular Conformation Generation. CoRR (2021)
Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
Learning Neural Generative Dynamics for Molecular Conformation Generation. ICLR (2021)
Hangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang, Hongyu Guo
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction. CoRR (2021)
Louis-Pascal A. C. Xhonneux, Andreea Deac, Petar Velickovic, Jian Tang
How to transfer algorithmic reasoning knowledge to learn new algorithms? CoRR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jian Tang