| Mattergen: a generative model for inorganic materials design C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, S Shysheya, ... arXiv preprint arXiv:2312.03687, 2023 | 48 | 2023 |
| The impact of large language models on scientific discovery: a preliminary study using gpt-4 MR AI4Science, MA Quantum arXiv preprint arXiv:2311.07361, 2023 | 25 | 2023 |
| Deep reinforcement learning with credit assignment for combinatorial optimization D Yan, J Weng, S Huang, C Li, Y Zhou, H Su, J Zhu Pattern Recognition 124, 108466, 2022 | 22 | 2022 |
| Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information Y Zhou, J Li, J Zhu International Conference on Learning Representations, 2020 | 21 | 2020 |
| Lazy-cfr: fast and near optimal regret minimization for extensive games with imperfect information Y Zhou, T Ren, J Li, D Yan, J Zhu arXiv preprint arXiv:1810.04433, 2018 | 14 | 2018 |
| Identify the Nash equilibrium in static games with random payoffs Y Zhou, J Li, J Zhu International Conference on Machine Learning, 4160-4169, 2017 | 12 | 2017 |
| Simultaneously learning stochastic and adversarial bandits with general graph feedback F Kong, Y Zhou, S Li International Conference on Machine Learning, 11473-11482, 2022 | 10 | 2022 |
| Online label aggregation: A variational bayesian approach C Hong, A Ghiassi, Y Zhou, R Birke, LY Chen Proceedings of the Web Conference 2021, 1904-1915, 2021 | 6 | 2021 |
| Racing thompson: An efficient algorithm for thompson sampling with non-conjugate priors Y Zhou, J Zhu, J Zhuo International Conference on Machine Learning, 6000-6008, 2018 | 6 | 2018 |
| Exploration analysis in finite-horizon turn-based stochastic games J Li, Y Zhou, T Ren, J Zhu Conference on Uncertainty in Artificial Intelligence, 201-210, 2020 | 5 | 2020 |
| Mattersim: A deep learning atomistic model across elements, temperatures and pressures H Yang, C Hu, Y Zhou, X Liu, Y Shi, J Li, G Li, Z Chen, S Chen, C Zeni, ... arXiv preprint arXiv:2405.04967, 2024 | 4 | 2024 |
| Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information Y Zhou, T Ren, J Li, D Yan, J Zhu arXiv preprint arXiv:1810.04433, 2018 | 4 | 2018 |
| Efficiently incorporating quintuple interactions into geometric deep learning force fields Z Wang, G Liu, Y Zhou, T Wang, B Shao Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| Selective verification strategy for learning from crowds T Tian, Y Zhou, J Zhu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 2 | 2018 |
| Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process X Zhou, L Wang, Y Zhou arXiv preprint arXiv:2403.04154, 2024 | 1 | 2024 |
| Overcoming the size limit of first principles molecular dynamics simulations with an in-distribution substructure embedding active learner L Kong, J Li, L Sun, H Yang, H Hao, C Chen, N Artrith, JAG Torres, Z Lu, ... arXiv preprint arXiv:2311.08177, 2023 | 1 | 2023 |
| Stochastic No-regret Learning for General Games with Variance Reduction Y Zhou, F Kong, S Li The Eleventh International Conference on Learning Representations, 2023 | 1 | 2023 |
| Supplementary Material: QuinNet: Efficiently Incorporating Quintuple Interactions into Geometric Deep Learning force Fields Z Wang, G Liu, Y Zhou, T Wang, B Shao | | |
| sampling with probability matching Y Zhou, J Zhu | | |
