5 citations · 12 across the 6 of their papers we have counts for
6 papers
Evaluation Methodology for Large Language Models for Multilingual Document Question and Answer
Adar Kahana, Jaya Susan Mathew, Said Bleik +2
With the widespread adoption of Large Language Models (LLMs), in this paper we investigate the multilingual capability of these models. Our preliminary results show that, translati…
Analysis of biologically plausible neuron models for regression with spiking neural networks
Mario De Florio, Adar Kahana, George Em Karniadakis
This paper explores the impact of biologically plausible neuron models on the performance of Spiking Neural Networks (SNNs) for regression tasks. While SNNs are widely recognized f…
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning
Qian Zhang, Chenxi Wu, Adar Kahana +4
We introduce a method to convert Physics-Informed Neural Networks (PINNs), commonly used in scientific machine learning, to Spiking Neural Networks (SNNs), which are expected to ha…
MyCrunchGPT: A chatGPT assisted framework for scientific machine learning
Varun Kumar, Leonard Gleyzer, Adar Kahana +2
Scientific Machine Learning (SciML) has advanced recently across many different areas in computational science and engineering. The objective is to integrate data and physics seaml…
ViTO: Vision Transformer-Operator
Oded Ovadia, Adar Kahana, Panos Stinis +2
We combine vision transformers with operator learning to solve diverse inverse problems described by partial differential equations (PDEs). Our approach, named ViTO, combines a U-N…
A physically-informed Deep-Learning approach for locating sources in a waveguide
Adar Kahana, Symeon Papadimitropoulos, Eli Turkel +1
Inverse source problems are central to many applications in acoustics, geophysics, non-destructive testing, and more. Traditional imaging methods suffer from the resolution limit,…