Shengchao Liu
Shengchao Liu
UC Berkeley, Caltech, Mila-UdeM, UWisc
Geverifieerd e-mailadres voor umontreal.ca - Homepage
Geciteerd door
Geciteerd door
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 31, 2018
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
S Liu, MF Demirel, Y Liang
Advances in Neural Information Processing Systems 32, 2019
Pre-training Molecular Graph Representation with 3D Geometry
S Liu, H Wang, W Liu, J Lasenby, H Guo, J Tang
International Conference on Learning Representation 2022, 2021
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning
S Liu, Y Liang, A Gitter
AAAI-SA 2019, 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, 3668-3679, 2020
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 59 (10), 4438-4449, 2019
Bad Global Minima Exist and SGD Can Reach Them
S Liu, D Papailiopoulos, D Achlioptas
Advances in Neural Information Processing Systems 33, 8543-8552, 2020
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 59 (1), 282-293, 2018
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
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
Molecular Geometry Pretraining with SE(3)-invariant Denoising Distance Matching
S Liu, H Guo, J Tang
International Conference on Learning Representation 2023, 2022
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, 8906-8920, 2022
Neural sentence ordering based on constraint graphs
Y Zhu, K Zhou, JY Nie, S Liu, Z Dou
Proceedings of the AAAI Conference on Artificial Intelligence 35 (16), 14656 …, 2021
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
arXiv preprint arXiv:2212.10789, 2022
Exploration on Deep Drug Discovery: Representation and Learning
S Liu
Thesis, University of Wisconsin-Madison, 2018
Evaluating self-supervised learning for molecular graph embeddings
H Wang, J Kaddour, S Liu, J Tang, M Kusner, J Lasenby, Q Liu
arXiv preprint arXiv:2206.08005, 2022
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
Attentive Walk-Aggregating Graph Neural Networks
MF Demirel, S Liu, S Garg, Z Shi, Y Liang
arXiv preprint arXiv:2110.02667, 2021
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 2023, 2023
Evaluating Scalable Supervised Learning for Synthesize-on-demand Chemical Libraries
M Alnammi, S Liu, SS Ericksen, GE Ananiev, AF Voter, S Guo, JL Keck, ...
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