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 | 119 | 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 | 44 | 2023 |
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 | 38 | 2024 |
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 | 29 | 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 | 23 | 2020 |
A generative model for inorganic materials design C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, Z Wang, ... Nature, 1-3, 2025 | 19 | 2025 |
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 | 13 | 2017 |
MatterGen: a generative model for inorganic materials design.(2023) C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, S Shysheya, ... arXiv preprint arXiv:2312.03687, 2023 | 11 | 2023 |
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 |
MatterSim: A deep learning atomistic model across elements, temperatures and pressures (2024) 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, 0 | 9 | |
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 | 7 | 2021 |
MatterSim: A Deep Learning Atomistic Model Across Elements H Yang, C Hu, Y Zhou, X Liu, Y Shi, J Li, G Li, Z Chen, S Chen, C Zeni, ... Temperatures and Pressures, 2024 | 6 | 2024 |
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 |
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, 77043-77055, 2023 | 5 | 2023 |
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 |
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 |
MatterGen: a generative model for inorganic materials design, arXiv C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, S Shysheya, ... Preprint.] Jan 29, 2024 | 3 | 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 | 2 | 2023 |
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 |