| Fourier Spectrum Discrepancies in Deep Network Generated Images T Dzanic, K Shah, F Witherden Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2019 | 123 | 2019 |
| Deep dive into machine learning density functional theory for materials science and chemistry L Fiedler, K Shah, M Bussmann, A Cangi Physical Review Materials 6 (4), 040301, 2022 | 61 | 2022 |
| Physics-Informed Neural Networks as Solvers for the Time-Dependent Schr\" odinger Equation K Shah, P Stiller, N Hoffmann, A Cangi Machine Learning and the Physical Sciences Workshop at the 36th conference …, 2022 | 5 | 2022 |
| Inferring student success predictors for CS1301x online course at Georgia Tech K Shah, M Bach, N Qin, A Liu, H Hussen, JY Lee, R Kadel Poster session presented at the American Society of Engineering Education …, 2017 | 2 | 2017 |
| Unsteady Lift Produced by a Flat-Plate Wing Translating Past Finite Obstacles KA Shah, MJ Ringuette AIAA Journal 62 (6), 2222-2234, 2024 | 1 | 2024 |
| The Unsteady Interaction of a Translating Wing with Finite Obstacles KA Shah State University of New York at Buffalo, 2021 | 1 | 2021 |
| Study of erosion and accretion from water and steam over pipe walls of condenser in a thermal power plant E Asok, KA Shah, JR Khan ASME International Mechanical Engineering Congress and Exposition 84560 …, 2020 | 1 | 2020 |
| Data science education in undergraduate physics: Lessons learned from a community of practice K Shah, J Butler, AV Knaub, A Zenginoğlu, W Ratcliff, M Soltanieh-Ha American Journal of Physics 92 (9), 655-662, 2024 | | 2024 |
| Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators K Shah, A Cangi arXiv preprint arXiv:2407.09628, 2024 | | 2024 |
| Inverting the Kohn–Sham equations with physics-informed machine learning V Martinetto, K Shah, A Cangi, A Pribram-Jones Machine Learning: Science and Technology 5 (1), 015050, 2024 | | 2024 |
| Physics-Informed Machine Learning for Addressing Challenges in Static and Time-Dependent Density Functional Theory K Shah, A Cangi Bulletin of the American Physical Society, 2024 | | 2024 |
| Machine-Learning for Static and Dynamic Electronic Structure Theory L Fiedler, K Shah, A Cangi Machine Learning in Molecular Sciences, 113-160, 2023 | | 2023 |
| XLDA: Linear Discriminant Analysis for Scaling Continual Learning to Extreme Classification at the Edge K Shah, V Veerendranath, A Hebbar, R Bhat arXiv preprint arXiv:2307.11317, 2023 | | 2023 |
| Accelerating Time-Dependent Density Functional Theory with Physics-Informed Neural Networks K Shah, A Cangi APS March Meeting Abstracts 2022, M01. 007, 2022 | | 2022 |
| Hierarchical Bayesian Modeling K Shah Bulletin of the American Physical Society 63, 2018 | | 2018 |
| Uncertainty Quantification of Machine Learned Density Functionals K Shah Georgia Institute of Technology, 2018 | | 2018 |
| Deep learning and the Schrödinger equation K SHAH | | |
Attila CangiCenter for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf在 hzdr.de 的电子邮件经过验证
