| Generative deep learning as a tool for inverse design of high-entropy refractory alloys A Debnath, AM Krajewski, H Sun, S Lin, M Ahn, W Li, S Priya, J Singh, ... arXiv preprint arXiv:2108.12019, 2021 | 27 | 2021 |
| Comparing forward and inverse design paradigms: A case study on refractory high-entropy alloys A Debnath, L Raman, W Li, AM Krajewski, M Ahn, S Lin, S Shang, ... Journal of Materials Research 38 (17), 4107-4117, 2023 | 2 | 2023 |
| Design and validation of refractory alloys using machine learning, CALPHAD, and experiments W Li, L Raman, A Debnath, M Ahn, S Lin, AM Krajewski, S Shang, S Priya, ... International Journal of Refractory Metals and Hard Materials 121, 106673, 2024 | 1 | 2024 |
| Investigating representation schemes for surrogate modeling of High Entropy Alloys A Debnath, WF Reinhart arXiv preprint arXiv:2301.00179, 2022 | 1 | 2022 |
| Leveraging multi-task model for improving mechanical property predictions of high entropy alloys (HEAs) A Debnath, W Reinhart Bulletin of the American Physical Society, 2024 | | 2024 |
| nimCSO: A Nim package for Compositional Space Optimization AM Krajewski, A Debnath, WF Reinhart, AM Beese, ZK Liu arXiv preprint arXiv:2403.02340, 2024 | | 2024 |
| Investigating representation schemes for surrogate modeling of High Entropy Alloys A Debnath, WF Reinhart Computational Materials Science 230, 112460, 2023 | | 2023 |
| An Interactive and Iterative Framework for Refractory Alloys Based on Machine Learning, Calphad and Experiments W Li, L Raman, M Ahn, A Debnath, S Lin, AM Krajewski, SL Shang, ... Calphad and Experiments, 0 | | |
