| Towards frequency-based explanation for robust cnn Z Wang, Y Yang, A Shrivastava, V Rawal, Z Ding arXiv preprint arXiv:2005.03141, 2020 | 45 | 2020 |
| Machine-learning accelerated geometry optimization in molecular simulation Y Yang, OA Jiménez-Negrón, JR Kitchin The Journal of Chemical Physics 154 (23), 2021 | 42 | 2021 |
| Simulating segregation in a ternary Cu–Pd–Au alloy with density functional theory, machine learning, and Monte Carlo simulations Y Yang, Z Guo, AJ Gellman, JR Kitchin The Journal of Physical Chemistry C 126 (4), 1800-1808, 2022 | 11 | 2022 |
| Semi-grand canonical Monte Carlo simulation of the acrolein induced surface segregation and aggregation of AgPd with machine learning surrogate models M Liu, Y Yang, JR Kitchin The Journal of Chemical Physics 154 (13), 2021 | 11 | 2021 |
| Neural Network Embeddings based Similarity Search Method for Atomistic Systems Y Yang, M Liu, JR Kitchin Digital Discovery, 2022 | 6 | 2022 |
| Evaluation of the degree of rate control via automatic differentiation Y Yang, SK Achar, JR Kitchin AIChE Journal 68 (6), e17653, 2022 | 4 | 2022 |
| Real‐Time Detection of Atmosphere Composition in Three‐Component Gas‐Phase Copolymerization of Olefins Z Zheng, Y Yang, K Huang, JJ Hu, S Jie, BG Li Macromolecular Reaction Engineering 12 (6), 1800042, 2018 | 2 | 2018 |
| Data-Driven Acceleration of Catalyst Modeling M Liu, Y Yang, J Kitchin 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Machine Learning-Accelerated Computing of Molecular and Catalytic Properties of Metallic Alloys Y Yang Carnegie Mellon University, 2022 | | 2022 |
