2 citations · 2 across the 3 of their papers we have counts for
6 papers
Differential Mamba
Nadav Schneider, Itamar Zimerman, Eliya Nachmani
Sequence models like Transformers and RNNs often overallocate attention to irrelevant context, leading to noisy intermediate representations. This degrades LLM capabilities by prom…
Reactor Optimization Benchmark by Reinforcement Learning
Deborah Schwarcz, Nadav Schneider, Gal Oren +1
Neutronic calculations for reactors are a daunting task when using Monte Carlo (MC) methods. As high-performance computing has advanced, the simulation of a reactor is nowadays mor…
MPIrigen: MPI Code Generation through Domain-Specific Language Models
Nadav Schneider, Niranjan Hasabnis, Vy A. Vo +9
The imperative need to scale computation across numerous nodes highlights the significance of efficient parallel computing, particularly in the realm of Message Passing Interface (…
MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
Tal Kadosh, Niranjan Hasabnis, Vy A. Vo +10
With easier access to powerful compute resources, there is a growing trend in AI for software development to develop large language models (LLMs) to address a variety of programmin…
Scope is all you need: Transforming LLMs for HPC Code
Tal Kadosh, Niranjan Hasabnis, Vy A. Vo +9
With easier access to powerful compute resources, there is a growing trend in the field of AI for software development to develop larger and larger language models (LLMs) to addres…
Explainable Multi-View Deep Networks Methodology for Experimental Physics
Nadav Schneider, Muriel Tzdaka, Galit Sturm +5
Physical experiments often involve multiple imaging representations, such as X-ray scans and microscopic images. Deep learning models have been widely used for supervised analysis…