Shengchao Liu

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Jian Tang (唐建）Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI ChairVerified email at hec.ca
Hongyu GuoSenior Research Scientist@NRC Canada, Adjunct Professor@University of OttawaVerified email at uottawa.ca
Anthony GitterAssociate Professor, University of Wisconsin-Madison; Morgridge Institute for ResearchVerified email at biostat.wisc.edu
Yingyu LiangUniversity of Wisconsin-MadisonVerified email at cs.wisc.edu
Dimitris PapailiopoulosAssociate Professor, University of Wisconsin-MadisonVerified email at papail.io
Mehmet F. DemirelPhD student at University of Wisconsin-MadisonVerified email at cs.wisc.edu
Spencer S. EricksenScientist, University of Wisconsin-MadisonVerified email at wisc.edu
Weiyang LiuUniversity of Cambridge & Max Planck Institute for Intelligent SystemsVerified email at cam.ac.uk
Chaowei XiaoUniversity of Wisconsin - MadisonVerified email at umich.edu
Weili NieNVIDIA ResearchVerified email at nvidia.com
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Dimitris AchlioptasProfessor of Computer Science, University of AthensVerified email at di.uoa.gr
Pierre-André NoëlServiceNow ResearchVerified email at servicenow.com
David VázquezServiceNow Research, ELLIS memberVerified email at servicenow.com
Zhao HaitengPeking UniversityVerified email at pku.edu.cn
Hannan XuDPhil student, University of OxfordVerified email at st-hughs.ox.ac.uk
Yanjing LiCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Jennifer ChayesProfessor, UC BerkeleyVerified email at jenniferchayes.com
Christian BorgsProfessor, UC BerkeleyVerified email at christianborgs.com
Omar M. YaghiJames and Neeltje Tretter Professor of Chemistry, UC BerkeleyVerified email at berkeley.edu

Shengchao Liu

UC Berkeley & Caltech

Verified email at umontreal.ca - Homepage

Machine Learning Statistical Learning Transfer Learning Geometric Learning Dynamic System


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Atomo: Communication-efficient learning via atomic sparsification H Wang, S Sievert, S Liu, Z Charles, D Papailiopoulos, S Wright NeurIPS 2018 31, 2018	334	2018
Pre-training Molecular Graph Representation with 3D Geometry S Liu, H Wang, W Liu, J Lasenby, H Guo, J Tang ICLR 2022, 2021	156	2021
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules S Liu, MF Demirel, Y Liang NeurIPS 2019 32, 2019	142	2019
Learning to navigate the synthetically accessible chemical space using reinforcement learning SK Gottipati, B Sattarov, S Niu, Y Pathak, H Wei, S Liu, S Blackburn, ... ICML 2021, 3668-3679, 2020	102	2020
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning S Liu, Y Liang, A Gitter AAAI-SA 2019, 2019	102	2019
Learning drug functions from chemical structures with convolutional neural networks and random forests JG Meyer, S Liu, IJ Miller, JJ Coon, A Gitter JCIM 2019 59 (10), 4438-4449, 2019	81	2019
Bad Global Minima Exist and SGD Can Reach Them S Liu, D Papailiopoulos, D Achlioptas NeurIPS 2020 33, 8543-8552, 2020	63	2020
Practical Model Selection for Prospective Virtual Screening S Liu, M Alnammi, SS Ericksen, AF Voter, GE Ananiev, JL Keck, ... JCIM 2019 59 (1), 282-293, 2018	62	2018
Torchdrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery Z Zhu, C Shi, Z Zhang, S Liu, M Xu, X Yuan, Y Zhang, J Chen, H Cai, J Lu, ... arXiv preprint arXiv:2202.08320, 2022	47	2022
Molgensurvey: A Systematic Survey in Machine Learning Models for Molecule Design Y Du, T Fu, J Sun, S Liu arXiv preprint arXiv:2203.14500, 2022	46	2022
Molecular Geometry Pretraining with SE(3)-invariant Denoising Distance Matching S Liu, H Guo, J Tang ICLR 2023, 2022	30	2022
Structured Multi-task Learning for Molecular Property Prediction S Liu, M Qu, Z Zhang, H Cai, J Tang AISTATS 2022, 8906-8920, 2022	22*	2022
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing S Liu, W Nie, C Wang, J Lu, Z Qiao, L Liu, J Tang, C Xiao, A Anandkumar Nature Machine Intelligence 2023, 2022	20	2022
Neural sentence ordering based on constraint graphs Y Zhu, K Zhou, JY Nie, S Liu, Z Dou AAAI 2021 35 (16), 14656-14664, 2021	16	2021
A Text-guided Protein Design Framework S Liu, Y Zhu, J Lu, Z Xu, W Nie, A Gitter, C Xiao, J Tang, H Guo, ... arXiv preprint arXiv:2302.04611, 2023	12	2023
Attentive Walk-Aggregating Graph Neural Networks MF Demirel, S Liu, S Garg, Z Shi, Y Liang TMLR 2022, 2021	10*	2021
Exploration on Deep Drug Discovery: Representation and Learning S Liu Thesis, University of Wisconsin-Madison, 2018	10	2018
Evaluating self-supervised learning for molecular graph embeddings H Wang, J Kaddour, S Liu, J Tang, M Kusner, J Lasenby, Q Liu NeurIPS 2023, 2022	9	2022
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining S Liu, W Du, Z Ma, H Guo, J Tang ICML 2023, 2023	7	2023
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain Feedback S Liu, J Wang, Y Yang, C Wang, L Liu, H Guo, C Xiao arXiv preprint arXiv:2305.18090, 2023	5	2023

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