Liu, Shengchao

46 publications

ICLR 2025 AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly Hongyu Guo, Yoshua Bengio, Shengchao Liu

ICLRW 2025 Flow Along the K-Amplitude for Generative Modeling Weitao Du, Shuning Chang, Jiasheng Tang, Yu Rong, Fan Wang, Shengchao Liu

NeurIPSW 2024 A Foundational Multi-Modal Knowledge Graph for Pancreatic Cancer Drug Effects Prediction Jingwen Hui, Shengchao Liu, Xiaohua Huang, Anima Anandkumar

NeurIPSW 2024 A Geometric Foundation Model for Crystalline Material Discovery Shengchao Liu, Liang Yan, Weitao Du, Zhuoxinran Li, Zhiling Zheng, Omar M. Yaghi, Christian Borgs, Hongyu Guo, Anima Anandkumar, Jennifer T Chayes

ICLRW 2024 A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Vignesh C Bhethanabotla, Nakul Rampal, Omar M. Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer T Chayes

ICMLW 2024 An Equivariant Flow Matching Framework for Learning Molecular Crystallization Shengchao Liu, Liang Yan, Hongyu Guo, Anima Anandkumar

NeurIPS 2024 CARE: A Benchmark Suite for the Classification and Retrieval of Enzymes Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Anima Anandkumar, Frances H. Arnold, Yisong Yue

ICLR 2024 Conversational Drug Editing Using Retrieval and Domain Feedback Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao

NeurIPSW 2024 Geometry-Text Multi-Modal Foundation Model for Reactivity-Oriented Molecule Editing Haorui Li, Shengchao Liu, Hongyu Guo, Anima Anandkumar

ICLR 2024 Improving Domain Generalization with Domain Relations Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn

NeurIPSW 2024 Language Models for Text-Guided Protein Evolution Zhanghan Ni, Shengchao Liu, Hongyu Guo, Anima Anandkumar

NeurIPSW 2024 Language Models for Text-Guided Protein Evolution Zhanghan Ni, Shengchao Liu, Anima Anandkumar

ICMLW 2024 Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design Shengchao Liu, Liang Yan, Weitao Du, Weiyang Liu, Hongyu Guo, Christian Borgs, Jennifer T Chayes, Anima Anandkumar

NeurIPSW 2024 Understanding Protein-DNA Interactions by Paying Attention to Protein and Genomics Foundation Models Dhruva Rajwade, Erica Wang, Aryan Satpathy, Alexander Brace, Hongyu Guo, Arvind Ramanathan, Shengchao Liu, Anima Anandkumar

NeurIPSW 2024 Understanding Protein-DNA Interactions by Paying Attention to Protein and Genomics Foundation Models Dhruva Rajwade, Erica Wang, Aryan Satpathy, Alexander Brace, Hongyu Guo, Arvind Ramanathan, Shengchao Liu, Anima Anandkumar

TMLR 2024 Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang

ICML 2023 A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-Modal Pretraining Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang

ICMLW 2023 ChatGPT-Powered Conversational Drug Editing Using Retrieval and Domain Feedback Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao

NeurIPSW 2023 ChatPathway: Conversational Large Language Models for Biology Pathway Detection Yanjing Li, Hannan Xu, Haiteng Zhao, Hongyu Guo, Shengchao Liu

NeurIPSW 2023 ChatPathway: Conversational Large Language Models for Biology Pathway Detection Yanjing Li, Hannan Xu, Haiteng Zhao, Hongyu Guo, Shengchao Liu

TMLR 2023 ChemSpacE: Interpretable and Interactive Chemical Space Exploration Yuanqi Du, Xian Liu, Nilay Mahesh Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou

NeurIPS 2023 Evaluating Self-Supervised Learning for Molecular Graph Embeddings Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

AAAI 2023 Flaky Performances When Pretraining on Relational Databases (Student Abstract) Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël

NeurIPS 2023 GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu

ICLR 2023 Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching Shengchao Liu, Hongyu Guo, Jian Tang

NeurIPS 2023 Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu

NeurIPS 2023 Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer Chayes, Hongyu Guo, Jian Tang

AISTATS 2022 Structured Multi-Task Learning for Molecular Property Prediction Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang

TMLR 2022 Attentive Walk-Aggregating Graph Neural Networks Mehmet F Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang

ICLRW 2022 ChemSpacE: Toward Steerable and Interpretable Chemical Space Exploration Yuanqi Du, Xian Liu, Shengchao Liu, Jieyu Zhang, Bolei Zhou

ICMLW 2022 Evaluating Self-Supervised Learned Molecular Graphs Hanchen Wang, Shengchao Liu, Jean Kaddour, Qi Liu, Jian Tang, Matt Kusner, Joan Lasenby

ICMLW 2022 Evaluating Self-Supervised Learned Molecular Graphs Hanchen Wang, Shengchao Liu, Jean Kaddour, Qi Liu, Jian Tang, Matt Kusner, Joan Lasenby

ICMLW 2022 Flaky Performances When Pre-Training on Relational Databases with a Plan for Future Characterization Efforts Shengchao Liu, David Vazquez, Jian Tang, Pierre-Andre Noel

NeurIPSW 2022 GraphCG: Unsupervised Discovery of Steerable Factors in Graphs Shengchao Liu, Chengpeng Wang, Weili Nie, Hanchen Wang, Jiarui Lu, Bolei Zhou, Jian Tang

ICLR 2022 Pre-Training Molecular Graph Representation with 3D Geometry Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

ICLRW 2022 Pre-Training Molecular Graph Representation with 3D Geometry Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

NeurIPSW 2022 Relational Out-of-Distribution Generalization Xinyu Yang, Xinyi Pan, Shengchao Liu, Huaxiu Yao

NeurIPSW 2021 Multi-Task Learning with Domain Knowledge for Molecular Property Prediction Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang

AAAI 2021 Neural Sentence Ordering Based on Constraint Graphs Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou

NeurIPS 2020 Bad Global Minima Exist and SGD Can Reach Them Shengchao Liu, Dimitris Papailiopoulos, Dimitris Achlioptas

ICML 2020 Learning to Navigate the Synthetically Accessible Chemical Space Using Reinforcement Learning Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio

ICML 2020 Learning to Navigate the Synthetically Accessible Chemical Space Using Reinforcement Learning Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio

ICMLW 2019 Bad Global Minima Exist and SGD Can Reach Them Shengchao Liu, Dimitris Papailiopoulos, Dimitris Achlioptas

AAAI 2019 Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning Shengchao Liu, Yingyu Liang, Anthony Gitter

NeurIPS 2019 N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules Shengchao Liu, Mehmet F Demirel, Yingyu Liang

NeurIPS 2018 ATOMO: Communication-Efficient Learning via Atomic Sparsification Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris Papailiopoulos, Stephen Wright