| Obstacle segmentation based on the wave equation and deep learning A Kahana, E Turkel, S Dekel, D Givoli Journal of Computational Physics 413, 109458, 2020 | 37 | 2020 |
| Vito: Vision transformer-operator O Ovadia, A Kahana, P Stinis, E Turkel, D Givoli, GE Karniadakis Computer Methods in Applied Mechanics and Engineering 428, 117109, 2024 | 28 | 2024 |
| A hybrid iterative numerical transferable solver (HINTS) for PDEs based on deep operator network and relaxation methods E Zhang, A Kahana, E Turkel, R Ranade, J Pathak, GE Karniadakis arXiv preprint arXiv:2208.13273, 2022 | 25 | 2022 |
| Mycrunchgpt: A llm assisted framework for scientific machine learning V Kumar, L Gleyzer, A Kahana, K Shukla, GE Karniadakis Journal of Machine Learning for Modeling and Computing 4 (4), 2023 | 21* | 2023 |
| System and method for improving machine learning models by detecting and removing inaccurate training data O Elisha, A Luttwak, H Yehuda, A Kahana, M Bechler-Speicher US Patent 11,636,389, 2023 | 20 | 2023 |
| Beyond the Courant-Friedrichs-Lewy condition: Numerical methods for the wave problem using deep learning O Ovadia, A Kahana, E Turkel, S Dekel Journal of Computational Physics 442, 110493, 2021 | 20 | 2021 |
| Ditto: Diffusion-inspired temporal transformer operator O Ovadia, E Turkel, A Kahana, GE Karniadakis arXiv preprint arXiv:2307.09072, 2023 | 14 | 2023 |
| Spiking neural operators for scientific machine learning A Kahana, Q Zhang, L Gleyzer, GE Karniadakis arXiv preprint arXiv:2205.10130, 2022 | 10* | 2022 |
| A physically-informed deep-learning model using time-reversal for locating a source from sparse and highly noisy sensors data A Kahana, E Turkel, S Dekel, D Givoli Journal of Computational Physics 470, 111592, 2022 | 9 | 2022 |
| On the geometry transferability of the hybrid iterative numerical solver for differential equations A Kahana, E Zhang, S Goswami, G Karniadakis, R Ranade, J Pathak Computational Mechanics 72 (3), 471-484, 2023 | 8 | 2023 |
| Artificial to spiking neural networks conversion for scientific machine learning Q Zhang, C Wu, A Kahana, Y Kim, Y Li, GE Karniadakis, P Panda arXiv preprint arXiv:2308.16372, 2023 | 8 | 2023 |
| System and method for improving machine learning models based on confusion error evaluation O Elisha, A Luttwak, H Yehuda, A Kahana, MB Speicher US Patent 11,636,387, 2023 | 8 | 2023 |
| Sms: Spiking marching scheme for efficient long time integration of differential equations Q Zhang, A Kahana, GE Karniadakis, P Stinis Journal of Computational Physics 516, 113363, 2024 | 6 | 2024 |
| Iterative vectoring for constructing data driven machine learning models O Elisha, A Luttwak, H Yehuda, A Kahana, M Bechler-Speicher US Patent App. 18/050,364, 2023 | 6 | 2023 |
| A high order compact time/space finite difference scheme for the 2D and 3D wave equation with a damping layer A Kahana, F Smith, E Turkel, S Tsynkov Journal of Computational Physics 460, 111161, 2022 | 6 | 2022 |
| A convolutional dispersion relation preserving scheme for the acoustic wave equation O Ovadia, A Kahana, E Turkel Applied Mathematics and Computation 461, 128317, 2024 | 4 | 2024 |
| Convective wave equation and time reversal process for source refocusing A Kahana, E Turkel, D Givoli Journal of theoretical and computational acoustics 26 (02), 1850016, 2018 | 4 | 2018 |
| Rethinking skip connections in Spiking Neural Networks with Time-To-First-Spike coding Y Kim, A Kahana, R Yin, Y Li, P Stinis, GE Karniadakis, P Panda Frontiers in Neuroscience 18, 1346805, 2024 | 3 | 2024 |
| A physically informed deep-learning approach for locating sources in a waveguide A Kahana, S Papadimitropoulos, E Turkel, D Batenkov The Journal of the Acoustical Society of America 154 (4), 2553-2563, 2023 | 3 | 2023 |
| Large scale scattering using fast solvers based on neural operators Z Zou, A Kahana, E Zhang, E Turkel, R Ranade, J Pathak, GE Karniadakis arXiv preprint arXiv:2405.12380, 2024 | 2 | 2024 |
Eli TurkelProfessor of Mathematics, Tel Aviv University在 post.tau.ac.il 的电子邮件经过验证
