| AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning R Magar, Y Wang, C Lorsung, C Liang, H Ramasubramanian, P Li, ... arXiv preprint arXiv:2111.15112, 2021 | 27 | 2021 |
| Mesh deep Q network: A deep reinforcement learning framework for improving meshes in computational fluid dynamics C Lorsung, A Barati Farimani AIP Advances 13 (1), 2023 | 9* | 2023 |
| Uncertainty-aware (una) bases for deep bayesian regression using multi-headed auxiliary networks S Thakur, C Lorsung, Y Yacoby, F Doshi-Velez, W Pan arXiv preprint arXiv:2006.11695, 2020 | 9 | 2020 |
| PyQMC: An all-Python real-space quantum Monte Carlo module in PySCF WA Wheeler, S Pathak, KG Kleiner, S Yuan, JNB Rodrigues, C Lorsung, ... The Journal of Chemical Physics 158 (11), 2023 | 6* | 2023 |
| Physics Informed Token Transformer for Solving Partial Differential Equations C Lorsung, Z Li, A Barati Farimani Machine Learning: Science and Technology, 2024 | 2* | 2024 |
| PICL: Physics Informed Contrastive Learning for Partial Differential Equations C Lorsung, AB Farimani arXiv preprint arXiv:2401.16327, 2024 | 2 | 2024 |
| Neural network predicts ion concentration profiles under nanoconfinement Z Cao, Y Wang, C Lorsung, A Barati Farimani The Journal of Chemical Physics 159 (9), 2023 | 1 | 2023 |
| Understanding uncertainty in bayesian deep learning C Lorsung arXiv preprint arXiv:2106.13055, 2021 | 1 | 2021 |
| Physics Informed Contrastive Learning for Homogeneous Partial Differential Equation Surrogate Modeling C Lorsung, A Barati Farimani Bulletin of the American Physical Society, 2024 | | 2024 |
| Improving Neural Operators with Physics Informed Token Transformers C Lorsung, Z Li, A Barati Farimani Bulletin of the American Physical Society, 2023 | | 2023 |
