Shengchao Liu

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Hongyu GuoSenior Research Scientist@NRC Canada, Adjunct Professor@University of OttawaDirección de correo verificada de uottawa.ca
Jian Tang (唐建）Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI ChairDirección de correo verificada de hec.ca
Anima AnandkumarCalifornia Institute of Technology and NVIDIADirección de correo verificada de caltech.edu
Anthony GitterAssociate Professor, University of Wisconsin-Madison; Morgridge Institute for ResearchDirección de correo verificada de biostat.wisc.edu
Yingyu LiangUW-MadisonDirección de correo verificada de cs.wisc.edu
Chaowei XiaoUniversity of Wisconsin - Madison/NVIDIADirección de correo verificada de umich.edu
Weili NieNVIDIA ResearchDirección de correo verificada de nvidia.com
Dimitris PapailiopoulosResearcher at Microsoft Research & Assoc. Professor at University of WisconsinDirección de correo verificada de papail.io
Jennifer ChayesProfessor, UC BerkeleyDirección de correo verificada de jenniferchayes.com
Christian BorgsProfessor, UC BerkeleyDirección de correo verificada de christianborgs.com
Mehmet F. DemirelPhD student at University of Wisconsin-MadisonDirección de correo verificada de cs.wisc.edu
Yanjing LiUniversity of WashingtonDirección de correo verificada de uw.edu
Weiyang LiuMax Planck Institute for Intelligent SystemsDirección de correo verificada de tuebingen.mpg.de
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARDirección de correo verificada de umontreal.ca
Hannan XuUniversity of OxfordDirección de correo verificada de bioch.ox.ac.uk
Haiteng ZhaoPeking UniversityDirección de correo verificada de pku.edu.cn
Spencer S. EricksenScientist, University of Wisconsin-MadisonDirección de correo verificada de wisc.edu
Yutao ZHURenmin University of ChinaDirección de correo verificada de ruc.edu.cn
Dimitris AchlioptasProfessor of Computer Science, University of AthensDirección de correo verificada de di.uoa.gr
Jian-Yun Nieuniversity of montrealDirección de correo verificada de iro.umontreal.ca

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Shengchao Liu

UC Berkeley

Dirección de correo verificada de berkeley.edu - Página principal

GenAI PhysAI Dynamics Physics and ML Pretraining


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Atomo: Communication-efficient learning via atomic sparsification H Wang, S Sievert, S Liu, Z Charles, D Papailiopoulos, S Wright Advances in Neural Information Processing Systems (NeurIPS) 2018 31, 2018	420	2018
Pre-training Molecular Graph Representation with 3D Geometry S Liu, H Wang, W Liu, J Lasenby, H Guo, J Tang International Conference on Learning Representations (ICLR) 2022, 2021	375	2021
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules S Liu, MF Demirel, Y Liang Advances in Neural Information Processing Systems (NeurIPS) 2019 32, 2019	225	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, ... International Conference on Machine Learning (ICML) 2021, 3668-3679, 2020	163	2020
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning S Liu, Y Liang, A Gitter AAAI-SA 2019, 2019	158	2019
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 5 (12), 1447-1457, 2023	144	2023
Learning drug functions from chemical structures with convolutional neural networks and random forests JG Meyer, S Liu, IJ Miller, JJ Coon, A Gitter Journal of Chemical Information and Modeling (JCIM) 2019 59 (10), 4438-4449, 2019	105	2019
Bad Global Minima Exist and SGD Can Reach Them S Liu, D Papailiopoulos, D Achlioptas Advances in Neural Information Processing Systems (NeurIPS) 2020 33, 8543-8552, 2020	94	2020
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	89	2022
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	82	2022
Molecular Geometry Pretraining with SE(3)-invariant Denoising Distance Matching S Liu, H Guo, J Tang International Conference on Learning Representations (ICLR) 2023, 2022	79	2022
Practical Model Selection for Prospective Virtual Screening S Liu, M Alnammi, SS Ericksen, AF Voter, GE Ananiev, JL Keck, ... Journal of Chemical Information and Modeling (JCIM) 2019 59 (1), 282-293, 2018	76	2018
Gimlet: A unified graph-text model for instruction-based molecule zero-shot learning H Zhao, S Liu, M Chang, H Xu, J Fu, Z Deng, L Kong, Q Liu Advances in Neural Information Processing Systems 36, 5850-5887, 2023	61	2023
A Text-guided Protein Design Framework S Liu, Y Li, Z Li, A Gitter, Y Zhu, J Lu, Z Xu, W Nie, A Ramanathan, C Xiao, ... arXiv preprint arXiv:2302.04611, 2023	60	2023
Shaping the water-harvesting behavior of metal–organic frameworks aided by fine-tuned GPT models Z Zheng, AH Alawadhi, S Chheda, SE Neumann, N Rampal, S Liu, ... Journal of the American Chemical Society 145 (51), 28284-28295, 2023	50	2023
Conversational Drug Editing Using Retrieval and Domain Feedback S Liu, J Wang, Y Yang, C Wang, L Liu, H Guo, C Xiao International Conference on Learning Representations (ICLR) 2024, 2023	47*	2023
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining S Liu, W Du, Z Ma, H Guo, J Tang International Conference on Machine Learning (ICML) 2023, 2023	35	2023
Structured Multi-task Learning for Molecular Property Prediction S Liu, M Qu, Z Zhang, H Cai, J Tang International Conference on Artificial Intelligence and Statistics (AISTATS …, 2022	35*	2022
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials S Liu, W Du, Y Li, Z Li, Z Zheng, C Duan, Z Ma, O Yaghi, A Anandkumar, ... Advances in Neural Information Processing Systems (NeurIPS) 2023, 2023	32	2023
Evaluating self-supervised learning for molecular graph embeddings H Wang, J Kaddour, S Liu, J Tang, M Kusner, J Lasenby, Q Liu Advances in Neural Information Processing Systems (NeurIPS) 2023, 2023	24	2023

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