| Molecular contrastive learning of representations via graph neural networks Y Wang, J Wang, Z Cao, A Barati Farimani Nature Machine Intelligence 4 (3), 279-287, 2022 | 373 | 2022 |
| Improving molecular contrastive learning via faulty negative mitigation and decomposed fragment contrast Y Wang, R Magar, C Liang, A Barati Farimani Journal of Chemical Information and Modeling 62 (11), 2713-2725, 2022 | 56 | 2022 |
| Moformer: self-supervised transformer model for metal–organic framework property prediction Z Cao, R Magar, Y Wang, A Barati Farimani Journal of the American Chemical Society 145 (5), 2958-2967, 2023 | 53 | 2023 |
| Efficient water desalination with graphene nanopores obtained using artificial intelligence Y Wang, Z Cao, A Barati Farimani npj 2D Materials and Applications 5 (1), 66, 2021 | 47 | 2021 |
| Airfoil GAN: encoding and synthesizing airfoils for aerodynamic shape optimization Y Wang, K Shimada, A Barati Farimani Journal of Computational Design and Engineering 10 (4), 1350-1362, 2023 | 36 | 2023 |
| TransPolymer: a Transformer-based language model for polymer property predictions C Xu, Y Wang, A Barati Farimani npj Computational Materials 9 (1), 64, 2023 | 35 | 2023 |
| AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning R Magar*, Y Wang*, C Lorsung*, C Liang, H Ramasubramanian, P Li, ... Machine Learning: Science and Technology, 2022 | 27 | 2022 |
| Crystal twins: self-supervised learning for crystalline material property prediction R Magar, Y Wang, A Barati Farimani npj Computational Materials 8 (1), 231, 2022 | 26 | 2022 |
| Prediction of GPCR activity using machine learning P Yadav, P Mollaei, Z Cao, Y Wang, AB Farimani Computational and Structural Biotechnology Journal 20, 2564-2573, 2022 | 19 | 2022 |
| Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy J Yoon, Z Cao, RK Raju, Y Wang, R Burnley, AJ Gellman, AB Farimani, ... Machine Learning: Science and Technology 2 (4), 045018, 2021 | 18 | 2021 |
| Predicting CO2 Absorption in Ionic Liquids with Molecular Descriptors and Explainable Graph Neural Networks Y Jian, Y Wang, A Barati Farimani ACS Sustainable Chemistry & Engineering 10 (50), 16681-16691, 2022 | 16 | 2022 |
| Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials Y Wang, C Xu, Z Li, AB Farimani Journal of Chemical Theory and Computation, 2023 | 13 | 2023 |
| Graph neural networks for molecules Y Wang, Z Li, A Barati Farimani Machine Learning in Molecular Sciences, 21-66, 2023 | 11 | 2023 |
| Three-dimensional ship hull encoding and optimization via deep neural networks Y Wang, J Joseph, TP Aniruddhan Unni, S Yamakawa, A Barati Farimani, ... Journal of Mechanical Design 144 (10), 101701, 2022 | 7 | 2022 |
| Adversarially robust imitation learning J Wang, Z Zhuang, Y Wang, H Zhao Conference on Robot Learning, 320-331, 2022 | 4 | 2022 |
| Bio-informed protein sequence generation for multi-class virus mutation prediction Y Wang, P Yadav, R Magar, AB Farimani bioRxiv, 2020.06. 11.146167, 2020 | 4 | 2020 |
| Generating molecular conformer fields Y Wang, AA Elhag, N Jaitly, JM Susskind, MA Bautista arXiv preprint arXiv:2311.17932, 2023 | 2 | 2023 |
| Manifold Diffusion Fields AA Elhag, Y Wang, JM Susskind, MA Bautista The International Conference on Learning Representations (ICLR) 2024, 2023 | 2 | 2023 |
| Neural Network Predicts Ion Concentration Profiles under Nanoconfinement Z Cao, Y Wang, C Lorsung, AB Farimani The Journal of Chemical Physics, 2023 | 1 | 2023 |
| Self-Supervised Representation Learning for Molecular Property Predictions Y Wang Carnegie Mellon University, 2023 | | 2023 |
