6 citations · 11 across the 15 of their papers we have counts for
15 papers
AutoLoop: Fast Visual SLAM Fine-tuning through Agentic Curriculum Learning
Assaf Lahiany, Oren Gal
Current visual SLAM systems face significant challenges in balancing computational efficiency with robust loop closure handling. Traditional approaches require careful manual tunin…
Robust Monocular Visual Odometry using Curriculum Learning
Assaf Lahiany, Oren Gal
Curriculum Learning (CL), drawing inspiration from natural learning patterns observed in humans and animals, employs a systematic approach of gradually introducing increasingly com…
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…
Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators
Yehonatan Fridman, Guy Tamir, Uri Steinitz +1
Monte Carlo (MC) simulations play a pivotal role in diverse scientific and engineering domains, with applications ranging from nuclear physics to materials science. Harnessing the…
The Landscape and Challenges of HPC Research and LLMs
Le Chen, Nesreen K. Ahmed, Akash Dutta +14
Recently, language models (LMs), especially large language models (LLMs), have revolutionized the field of deep learning. Both encoder-decoder models and prompt-based techniques ha…
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 (…