Shengchao Liu

According to our database, Shengchao Liu authored at least 52 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

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

Trans. Mach. Learn. Res., 2024

Targetless External Reference Calibration of LiDAR and Camera in Autonomous Driving Environment.

Hao Wu, Yang Liu, Hongqian Huang, Jie Li, Qijing Lin, Shengchao Liu

IEEE Trans. Instrum. Meas., 2024

Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design.

Shengchao Liu, Divin Yan, Weitao Du, Weiyang Liu, Zhuoxinran Li, Hongyu Guo, Christian Borgs, Jennifer T. Chayes, Anima Anandkumar

CoRR, 2024

Does DetectGPT Fully Utilize Perturbation? Bridge Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better.

Shengchao Liu, Xiaoming Liu, Yichen Wang, Zehua Cheng, Chengzhengxu Li, Zhaohan Zhang, Yu Lan, Chao Shen

CoRR, 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 Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer T. Chayes

CoRR, 2024

A quatum inspired neural network for geometric modeling.

Weitao Du, Shengchao Liu, Xuecang Zhang

CoRR, 2024

MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization.

Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Väinö Hatanpää, Varuni Katti Sastry, Huihuo Zheng, Logan T. Ward, Servesh Muralidharan, Archit Vasan, Bharat Kale, Carla M. Mann, Heng Ma, Yun-Hsuan Cheng, Yuliana Zamora, Shengchao Liu, Chaowei Xiao, Murali Emani, Tom Gibbs, Mahidhar Tatineni, Deepak Canchi, Jerome Mitchell, Koichi Yamada, Maria Garzaran, Michael E. Papka, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan

Proceedings of the International Conference for High Performance Computing, 2024

Improving Domain Generalization with Domain Relations.

Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Conversational Drug Editing Using Retrieval and Domain Feedback.

Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better.

Shengchao Liu, Xiaoming Liu, Yichen Wang, Zehua Cheng, Chengzhengxu Li, Zhaohan Zhang, Yu Lan, Chao Shen

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Multi-modal molecule structure-text model for text-based retrieval and editing.

Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Animashree Anandkumar

Nat. Mac. Intell., December, 2023

Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries.

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

J. Chem. Inf. Model., September, 2023

ChemSpacE: Interpretable and Interactive Chemical Space Exploration.

Yuanqi Du, Xian Liu, Nilay Mahesh Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou

Trans. Mach. Learn. Res., 2023

Scientific discovery in the age of artificial intelligence.

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

Nat., 2023

GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning.

Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhi-Hong Deng, Lingpeng Kong, Qi Liu

CoRR, 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

CoRR, 2023

A Text-guided Protein Design Framework.

Shengchao Liu, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Anthony Gitter, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar

CoRR, 2023

Leveraging Domain Relations for Domain Generalization.

Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn

CoRR, 2023

GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning.

Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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 T. Chayes, Hongyu Guo, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion.

Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining.

Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang

Proceedings of the International Conference on Machine Learning, 2023

Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching.

Shengchao Liu, Hongyu Guo, Jian Tang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Empirical Study of Retrieval-Enhanced Graph Neural Networks.

Dingmin Wang, Shengchao Liu, Hanchen Wang, Bernardo Cuenca Grau, Linfeng Song, Jian Tang, Le Song, Qi Liu

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Flaky Performances When Pretraining on Relational Databases (Student Abstract).

Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Attentive Walk-Aggregating Graph Neural Networks.

Mehmet Furkan Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang

Trans. Mach. Learn. Res., 2022

Flaky Performances when Pretraining on Relational Databases.

Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël

CoRR, 2022

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt J. Kusner, Joan Lasenby, Qi Liu

CoRR, 2022

Augmenting Message Passing by Retrieving Similar Graphs.

Dingmin Wang, Shengchao Liu, Hanchen Wang, Linfeng Song, Jian Tang, Song Le, Bernardo Cuenca Grau, Qi Liu

CoRR, 2022

MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design.

Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu

CoRR, 2022

TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery.

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

CoRR, 2022

Pre-training Molecular Graph Representation with 3D Geometry.

Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Structured Multi-task Learning for Molecular Property Prediction.

Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

An Analysis of Attentive Walk-Aggregating Graph Neural Networks.

Mehmet Furkan Demirel, Shengchao Liu, Siddhant Garg, Yingyu Liang

CoRR, 2021

BERT4SO: Neural Sentence Ordering by Fine-tuning BERT.

Yutao Zhu, Jian-Yun Nie, Kun Zhou, Shengchao Liu, Pan Du

CoRR, 2021

Neural Sentence Ordering Based on Constraint Graphs.

Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Achieving User-Defined Location Privacy Preservation Using a P2P System.

Shengchao Liu, Jessie Hui Wang, Jilong Wang, Qianli Zhang

IEEE Access, 2020

Bad Global Minima Exist and SGD Can Reach Them.

Shengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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, Simon Blackburn, Karam M. J. Thomas, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

An Adaptive Online Scheme for Scheduling and Resource Enforcement in Storm.

Shengchao Liu, Jianping Weng, Jessie Hui Wang, Changqing An, Yipeng Zhou, Jilong Wang

IEEE/ACM Trans. Netw., 2019

Learning Drug Functions from Chemical Structures with Convolutional Neural Networks and Random Forests.

Jesse G. Meyer, Shengchao Liu, Ian J. Miller, Joshua J. Coon, Anthony Gitter

J. Chem. Inf. Model., 2019

Practical Model Selection for Prospective Virtual Screening.

Shengchao Liu, Moayad Alnammi, Spencer S. Ericksen, Andrew F. Voter, Gene E. Ananiev, James L. Keck, F. Michael Hoffmann, Scott A. Wildman, Anthony Gitter

J. Chem. Inf. Model., 2019

N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules.

Shengchao Liu, Mehmet Furkan Demirel, Yingyu Liang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Evaluation of Hybrid Si/SiC Three-Level Active Neutral-Point-Clamped Inverters.

Li Zhang, Shengchao Liu, Guang Chen, Xingjian Yang

Proceedings of the 28th IEEE International Symposium on Industrial Electronics, 2019

A Generalized Moving Average Filter for Active Power Filter Applications.

Yalan Gu, Shengchao Liu, Dong Wang, Li Zhang

Proceedings of the 28th IEEE International Symposium on Industrial Electronics, 2019

WRT: Constructing Users' Web Request Trees from HTTP Header Logs.

Shengchao Liu, Jilong Wang, Hui Wang, Haibo Wang, Ya Liu

Proceedings of the 2019 IEEE International Conference on Communications, 2019

Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning.

Shengchao Liu, Yingyu Liang, Anthony Gitter

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Dissecting persistent instability of web service: A joint perspective of server schedule dynamics and path latency.

Jing'an Xue, Jilong Wang, Shengchao Liu, Xiulin Ma, Haibo Wang

Int. J. Commun. Syst., 2018

N-Gram Graph, A Novel Molecule Representation.

Shengchao Liu, Thevaa Chandereng, Yingyu Liang

CoRR, 2018

ATOMO: Communication-efficient Learning via Atomic Sparsification.

Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Multi-dimension Measurement Study of a Large Scale Campus WiFi Network.

Congcong Miao, Jilong Wang, Hui Wang, Jun Zhang, Weiwei Zhou, Shengchao Liu

Proceedings of the 43rd IEEE Conference on Local Computer Networks, 2018