Shengchao Liu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 61

Top Topics

Active Power Filter

Constraint Graph

Top Venues

Publications

Shengchao Liu, Xiaoming Liu, Yichen Wang, Zehua Cheng, Chengzhengxu Li, Zhaohan Zhang, Yu Lan, Chao Shen
Does DetectGPT Fully Utilize Perturbation? Selective Perturbation on Model-Based Contrastive Learning Detector would be Better. 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. Trans. Mach. Learn. Res. 2024 (2024)
Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao
Conversational Drug Editing Using Retrieval and Domain Feedback. ICLR (2024)
Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Vignesh C. Bhethanabotla, Nakul Rampal, Omar Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer T. Chayes
A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics. CoRR (2024)
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
Improving Domain Generalization with Domain Relations. ICLR (2024)
Shengchao Liu, Xiaoming Liu, Yichen Wang, Zehua Cheng, Chengzhengxu Li, Zhaohan Zhang, Yu Lan, Chao Shen
Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better. ACL (1) (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)
Weitao Du, Shengchao Liu, Hongyu Guo
A quatum inspired neural network for geometric modeling. CoRR (2024)
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)
Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning. NeurIPS (2023)
Moayad Alnammi, Shengchao Liu, Spencer S. Ericksen, Gene E. Ananiev, Andrew F. Voter, Song Guo, James L. Keck, F. Michael Hoffmann, Scott A. Wildman, Anthony Gitter
Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries. J. Chem. Inf. Model. 63 (17) (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)
Yuanqi Du, Xian Liu, Nilay Mahesh Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou
ChemSpacE: Interpretable and Interactive Chemical Space Exploration. Trans. Mach. Learn. Res. 2023 (2023)
Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. NeurIPS (2023)
Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhi-Hong Deng, Lingpeng Kong, Qi Liu
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning. CoRR (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)
Dingmin Wang, Shengchao Liu, Hanchen Wang, Bernardo Cuenca Grau, Linfeng Song, Jian Tang, Le Song, Qi Liu
An Empirical Study of Retrieval-Enhanced Graph Neural Networks. ECAI (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, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain Feedback. CoRR (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)
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)
Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhiming Ma, Shengchao Liu
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. CoRR (2023)
Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu
Evaluating Self-Supervised Learning for Molecular Graph Embeddings. NeurIPS (2023)
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
Leveraging Domain Relations for Domain Generalization. CoRR (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)
Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang
Structured Multi-task Learning for Molecular Property Prediction. 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)
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)
Shengchao Liu, Hongyu Guo, Jian Tang
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching. CoRR (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)
Mehmet Furkan Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang
Attentive Walk-Aggregating Graph Neural Networks. Trans. Mach. Learn. Res. 2022 (2022)
Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. CoRR (2022)
Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël
Flaky Performances when Pretraining on Relational Databases. CoRR (2022)
Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
Pre-training Molecular Graph Representation with 3D Geometry. ICLR (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)
Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou
Neural Sentence Ordering Based on Constraint Graphs. AAAI (2021)
Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou
Neural Sentence Ordering Based on Constraint Graphs. CoRR (2021)
Yutao Zhu, Jian-Yun Nie, Kun Zhou, Shengchao Liu, Pan Du
BERT4SO: Neural Sentence Ordering by Fine-tuning BERT. CoRR (2021)
Mehmet Furkan Demirel, Shengchao Liu, Siddhant Garg, Yingyu Liang
An Analysis of Attentive Walk-Aggregating Graph Neural Networks. CoRR (2021)
Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
Pre-training Molecular Graph Representation with 3D Geometry. CoRR (2021)
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Simon Blackburn, Karam M. J. Thomas, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. ICML (2020)
Shengchao Liu, Jessie Hui Wang, Jilong Wang, Qianli Zhang
Achieving User-Defined Location Privacy Preservation Using a P2P System. IEEE Access 8 (2020)
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Karam M. J. Thomas, Simon Blackburn, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. CoRR (2020)
Shengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas
Bad Global Minima Exist and SGD Can Reach Them. NeurIPS (2020)
Shengchao Liu, Moayad Alnammi, Spencer S. Ericksen, Andrew F. Voter, Gene E. Ananiev, James L. Keck, F. Michael Hoffmann, Scott A. Wildman, Anthony Gitter
Practical Model Selection for Prospective Virtual Screening. J. Chem. Inf. Model. 59 (1) (2019)
Li Zhang, Shengchao Liu, Guang Chen, Xingjian Yang
Evaluation of Hybrid Si/SiC Three-Level Active Neutral-Point-Clamped Inverters. ISIE (2019)
Shengchao Liu, Yingyu Liang, Anthony Gitter
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning. AAAI (2019)
Shengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas
Bad Global Minima Exist and SGD Can Reach Them. CoRR (2019)
Yalan Gu, Shengchao Liu, Dong Wang, Li Zhang
A Generalized Moving Average Filter for Active Power Filter Applications. ISIE (2019)
Shengchao Liu, Jianping Weng, Jessie Hui Wang, Changqing An, Yipeng Zhou, Jilong Wang
An Adaptive Online Scheme for Scheduling and Resource Enforcement in Storm. IEEE/ACM Trans. Netw. 27 (4) (2019)
Jesse G. Meyer, Shengchao Liu, Ian J. Miller, Joshua J. Coon, Anthony Gitter
Learning Drug Functions from Chemical Structures with Convolutional Neural Networks and Random Forests. J. Chem. Inf. Model. 59 (10) (2019)
Shengchao Liu, Mehmet Furkan Demirel, Yingyu Liang
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules. NeurIPS (2019)
Shengchao Liu, Jilong Wang, Hui Wang, Haibo Wang, Ya Liu
WRT: Constructing Users' Web Request Trees from HTTP Header Logs. ICC (2019)
Congcong Miao, Jilong Wang, Hui Wang, Jun Zhang, Weiwei Zhou, Shengchao Liu
A Multi-dimension Measurement Study of a Large Scale Campus WiFi Network. LCN (2018)
Shengchao Liu, Thevaa Chandereng, Yingyu Liang
N-Gram Graph, A Novel Molecule Representation. CoRR (2018)
Jing'an Xue, Jilong Wang, Shengchao Liu, Xiulin Ma, Haibo Wang
Dissecting persistent instability of web service: A joint perspective of server schedule dynamics and path latency. Int. J. Commun. Syst. 31 (7) (2018)
Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary B. Charles, Dimitris S. Papailiopoulos, Stephen J. Wright
ATOMO: Communication-efficient Learning via Atomic Sparsification. CoRR (2018)
Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary B. Charles, Dimitris S. Papailiopoulos, Stephen J. Wright
ATOMO: Communication-efficient Learning via Atomic Sparsification. NeurIPS (2018)