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Shengchao Liu
Shengchao Liu
UC Berkeley
Bestätigte E-Mail-Adresse bei berkeley.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
4212018
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
4092021
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
2342019
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
1702020
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
1672023
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning
S Liu, Y Liang, A Gitter
AAAI-SA 2019, 2019
1612019
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
1062019
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
1032020
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
932022
Molecular Geometry Pretraining with SE(3)-invariant Denoising Distance Matching
S Liu, H Guo, J Tang
International Conference on Learning Representations (ICLR) 2023, 2022
872022
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
862022
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
81*2023
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
782018
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
652023
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
572023
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
57*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
392023
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
39*2022
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
282023
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
262023
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