Obstacle segmentation based on the wave equation and deep learning. - Adar Kahana; Eli Turkel; Shai Dekel; Dan Givoli (J. Comput. Phys., 2020)

Beyond the Courant-Friedrichs-Lewy condition: Numerical methods for the wave problem using deep learning. - Oded Ovadia; Adar Kahana; Eli Turkel; Shai Dekel (J. Comput. Phys., 2021)

Function Regression using Spiking DeepONet. - Adar Kahana; Qian Zhang; Leonard Gleyzer; George Em Karniadakis (CoRR, 2022)

A physically-informed Deep-Learning approach for locating sources in a waveguide. - Adar Kahana; Symeon Papadimitropoulos; Eli Turkel; Dmitry Batenkov (CoRR, 2022)

A Hybrid Iterative Numerical Transferable Solver (HINTS) for PDEs Based on Deep Operator Network and Relaxation Methods. - Enrui Zhang; Adar Kahana; Eli Turkel; Rishikesh Ranade; Jay Pathak; George Em Karniadakis (CoRR, 2022)

On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. - Adar Kahana; Enrui Zhang; Somdatta Goswami; George Em Karniadakis; Rishikesh Ranade; Jay Pathak (CoRR, 2022)

SMS: Spiking Marching Scheme for Efficient Long Time Integration of Differential Equations. - Qian Zhang; Adar Kahana; George Em Karniadakis; Panos Stinis (CoRR, 2022)

A high order compact time/space finite difference scheme for the 2D and 3D wave equation with a damping layer. - Adar Kahana; Fouche Smith; Eli Turkel; Semyon Tsynkov (J. Comput. Phys., 2022)

A physically-informed deep-learning model using time-reversal for locating a source from sparse and highly noisy sensors data. - Adar Kahana; Eli Turkel; Shai Dekel; Dan Givoli (J. Comput. Phys., 2022)

MessageNet: Message Classification using Natural Language Processing and Meta-data. - Adar Kahana; Oren Elisha (CoRR, 2023)

ViTO: Vision Transformer-Operator. - Oded Ovadia; Adar Kahana; Panos Stinis; Eli Turkel; George Em Karniadakis (CoRR, 2023)

CrunchGPT: A chatGPT assisted framework for scientific machine learning. - Varun Kumar; Leonard Gleyzer; Adar Kahana; Khemraj Shukla; George Em Karniadakis (CoRR, 2023)

Understanding the Efficacy of U-Net & Vision Transformer for Groundwater Numerical Modelling. - Maria Luisa Taccari; Oded Ovadia; He Wang 002; Adar Kahana; Xiaohui Chen; Peter K. Jimack (CoRR, 2023)

DiTTO: Diffusion-inspired Temporal Transformer Operator. - Oded Ovadia; Eli Turkel; Adar Kahana; George Em Karniadakis (CoRR, 2023)

Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning. - Qian Zhang; Chenxi Wu; Adar Kahana; Youngeun Kim; Yuhang Li 001; George Em Karniadakis; Priyadarshini Panda (CoRR, 2023)

Spiking Physics-Informed Neural Networks on Loihi 2. - Bradley H. Theilman; Qian Zhang; Adar Kahana; Eric C. Cyr; Nathaniel Trask; James B. Aimone; George Em Karniadakis (NICE, 2024)

Analysis of biologically plausible neuron models for regression with spiking neural networks. - Mario De Florio; Adar Kahana; George Em Karniadakis (CoRR, 2024)

Evaluation Methodology for Large Language Models for Multilingual Document Question and Answer. - Adar Kahana; Jaya Susan Mathew; Said Bleik; Jeremy Reynolds; Oren Elisha (CoRR, 2024)

Large scale scattering using fast solvers based on neural operators. - Zongren Zou; Adar Kahana; Enrui Zhang; Eli Turkel; Rishikesh Ranade; Jay Pathak; George Em Karniadakis (CoRR, 2024)

Blending neural operators and relaxation methods in PDE numerical solvers. - Enrui Zhang; Adar Kahana; Alena Kopanicáková; Eli Turkel; Rishikesh Ranade; Jay Pathak; George Em Karniadakis (Nat. Mac. Intell., 2024)

A convolutional dispersion relation preserving scheme for the acoustic wave equation. - Oded Ovadia; Adar Kahana; Eli Turkel (Appl. Math. Comput., 2024)

Artificial to Spiking Neural Networks Conversion with Calibration in Scientific Machine Learning. - Qian Zhang; Chenxi Wu; Adar Kahana; George Em Karniadakis; Youngeun Kim; Yuhang Li 001; Priyadarshini Panda (SIAM J. Sci. Comput., 2025)