| 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 | 233 | 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 | 72 | 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 | 56 | 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 | 49 | 2019 |
| Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning S Liu, Y Liang, A Gitter https://aaai.org/ojs/index.php/AAAI/article/view/5125, 2019 | 49 | 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 | 40 | 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 | 39 | 2018 |
| Pre-training molecular graph representation with 3d geometry S Liu, H Wang, W Liu, J Lasenby, H Guo, J Tang arXiv preprint arXiv:2110.07728, 2021 | 26 | 2021 |
| 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 | 10 | 2021 |
| EXPLORATION ON DEEP DRUG DISCOVERY: REPRESENTATION AND LEARNING S Liu Thesis, University of Wisconsin-Madison, 2018 | 10 | 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 | 5 | 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 | 4 | 2022 |
| An analysis of attentive walk-aggregating graph neural networks MF Demirel, S Liu, S Garg, Y Liang arXiv preprint arXiv:2110.02667, 2021 | 4 | 2021 |
| 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 | 2 | 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 | 2* | 2022 |
| ChemSpacE: Toward Steerable and Interpretable Chemical Space Exploration Y Du, X Liu, S Liu, J Zhang, B Zhou ICLR2022 Machine Learning for Drug Discovery, 2022 | 2* | 2022 |
| Evaluating scalable supervised learning for synthesize-on-demand chemical libraries M Alnammi, S Liu, SS Ericksen, GE Ananiev, AF Voter, S Guo, JL Keck, ... | 2 | 2021 |
| Structured Multi-View Representations for Drug Combinations S Liu, A Deac, Z Zhu, J Tang NeurIPS 2020 ML for Molecules Workshop, 2020 | 2 | 2020 |
| BERT4so: Neural sentence ordering by fine-tuning BERT Y Zhu, JY Nie, K Zhou, S Liu, Y Ling, P Du arXiv preprint arXiv:2103.13584, 2021 | 1 | 2021 |
| Molecular Geometry Pretraining with SE (3)-Invariant Denoising Distance Matching S Liu, H Guo, J Tang arXiv preprint arXiv:2206.13602, 2022 | | 2022 |
Anthony GitterAssociate Professor, University of Wisconsin-Madison; Morgridge Institute for ResearchVerified email at biostat.wisc.edu
