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ORCIDShengchao Liu
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2020 – today
- 2024
[j12]Hao Wu, Yang Liu, Hongqian Huang, Jie Li, Qijing Lin, Shengchao Liu:
Targetless External Reference Calibration of LiDAR and Camera in Autonomous Driving Environment. IEEE Trans. Instrum. Meas. 73: 1-9 (2024)- [j11]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) - [c23]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: 1874-1889 - [c22]Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao:
Conversational Drug Editing Using Retrieval and Domain Feedback. ICLR 2024 - [c21]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Improving Domain Generalization with Domain Relations. ICLR 2024 - [i28]Weitao Du, Shengchao Liu, Xuecang Zhang:
A quatum inspired neural network for geometric modeling. CoRR abs/2401.01801 (2024) - [i27]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 abs/2401.15122 (2024) - [i26]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 abs/2401.17123 (2024) - [i25]Shengchao Liu, Xiaoming Liu, Yichen Wang, Zehua Cheng, Chengzhengxu Li, Zhaohan Zhang, Yu Lan, Chao Shen:
Does DetectGPT Fully Utilize Perturbation? Bridge Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better. CoRR abs/2402.00263 (2024) - [i24]Shengchao Liu, Divin Yan, Weitao Du, Weiyang Liu, Zhuoxinran Li, Hongyu Guo, Christian Borgs, Jennifer T. Chayes, Anima Anandkumar:
Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design. CoRR abs/2409.10584 (2024) - 2023
- [j10]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): 5513-5528 (2023) - [j9]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): 1447-1457 (2023) - [j8]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): 47-60 (2023) - [j7]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) - [c20]Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël:
Flaky Performances When Pretraining on Relational Databases (Student Abstract). AAAI 2023: 16266-16267 - [c19]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: 2443-2450 - [c18]Shengchao Liu, Hongyu Guo, Jian Tang:
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching. ICLR 2023 - [c17]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: 21497-21526 - [c16]Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu:
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. NeurIPS 2023 - [c15]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 - [c14]Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu:
Evaluating Self-Supervised Learning for Molecular Graph Embeddings. NeurIPS 2023 - [c13]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 - [i23]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Leveraging Domain Relations for Domain Generalization. CoRR abs/2302.02609 (2023) - [i22]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 abs/2302.04611 (2023) - [i21]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 abs/2305.18090 (2023) - [i20]Shengchao Liu, Weitao Du, Zhiming Ma, Hongyu Guo, Jian Tang:
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. CoRR abs/2305.18407 (2023) - [i19]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 abs/2306.09375 (2023) - [i18]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 abs/2306.13089 (2023) - [i17]Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhiming Ma, Shengchao Liu:
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. CoRR abs/2312.03475 (2023) - 2022
- [j6]Mehmet Furkan Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang:
Attentive Walk-Aggregating Graph Neural Networks. Trans. Mach. Learn. Res. 2022 (2022) - [c12]Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang:
Structured Multi-task Learning for Molecular Property Prediction. AISTATS 2022: 8906-8920 - [c11]Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang:
Pre-training Molecular Graph Representation with 3D Geometry. ICLR 2022 - [i16]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 abs/2202.08320 (2022) - [i15]Shengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang:
Structured Multi-task Learning for Molecular Property Prediction. CoRR abs/2203.04695 (2022) - [i14]Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu:
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. CoRR abs/2203.14500 (2022) - [i13]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 abs/2206.00362 (2022) - [i12]Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt J. Kusner, Joan Lasenby, Qi Liu:
Evaluating Self-Supervised Learning for Molecular Graph Embeddings. CoRR abs/2206.08005 (2022) - [i11]Shengchao Liu, Hongyu Guo, Jian Tang:
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching. CoRR abs/2206.13602 (2022) - [i10]Shengchao Liu, David Vázquez, Jian Tang, Pierre-André Noël:
Flaky Performances when Pretraining on Relational Databases. CoRR abs/2211.05213 (2022) - [i9]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 abs/2212.10789 (2022) - 2021
- [c10]Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou:
Neural Sentence Ordering Based on Constraint Graphs. AAAI 2021: 14656-14664 - [i8]Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou:
Neural Sentence Ordering Based on Constraint Graphs. CoRR abs/2101.11178 (2021) - [i7]Yutao Zhu, Jian-Yun Nie, Kun Zhou, Shengchao Liu, Pan Du:
BERT4SO: Neural Sentence Ordering by Fine-tuning BERT. CoRR abs/2103.13584 (2021) - [i6]Mehmet Furkan Demirel, Shengchao Liu, Siddhant Garg, Yingyu Liang:
An Analysis of Attentive Walk-Aggregating Graph Neural Networks. CoRR abs/2110.02667 (2021) - [i5]Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang:
Pre-training Molecular Graph Representation with 3D Geometry. CoRR abs/2110.07728 (2021) - 2020
- [j5]Shengchao Liu, Jessie Hui Wang, Jilong Wang, Qianli Zhang:
Achieving User-Defined Location Privacy Preservation Using a P2P System. IEEE Access 8: 45895-45912 (2020) - [c9]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: 3668-3679 - [c8]Shengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas:
Bad Global Minima Exist and SGD Can Reach Them. NeurIPS 2020 - [i4]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 abs/2004.12485 (2020)
2010 – 2019
- 2019
- [j4]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): 282-293 (2019) - [j3]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): 4438-4449 (2019) - [j2]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): 1373-1386 (2019) - [c7]Shengchao Liu, Yingyu Liang, Anthony Gitter:
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning. AAAI 2019: 9977-9978 - [c6]Shengchao Liu, Jilong Wang, Hui Wang, Haibo Wang, Ya Liu:
WRT: Constructing Users' Web Request Trees from HTTP Header Logs. ICC 2019: 1-7 - [c5]Yalan Gu, Shengchao Liu, Dong Wang, Li Zhang:
A Generalized Moving Average Filter for Active Power Filter Applications. ISIE 2019: 428-433 - [c4]Li Zhang, Shengchao Liu, Guang Chen, Xingjian Yang:
Evaluation of Hybrid Si/SiC Three-Level Active Neutral-Point-Clamped Inverters. ISIE 2019: 840-845 - [c3]Shengchao Liu, Mehmet Furkan Demirel, Yingyu Liang:
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules. NeurIPS 2019: 8464-8476 - [i3]Shengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas:
Bad Global Minima Exist and SGD Can Reach Them. CoRR abs/1906.02613 (2019) - 2018
- [j1]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) - [c2]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: 351-359 - [c1]Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright:
ATOMO: Communication-efficient Learning via Atomic Sparsification. NeurIPS 2018: 9872-9883 - [i2]Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright:
ATOMO: Communication-efficient Learning via Atomic Sparsification. CoRR abs/1806.04090 (2018) - [i1]Shengchao Liu, Thevaa Chandereng, Yingyu Liang:
N-Gram Graph, A Novel Molecule Representation. CoRR abs/1806.09206 (2018)
Coauthor Index
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