27 citations · 103 across the 19 of their papers we have counts for
3 papers · 1 filter
Multimarginal flow matching with optimal transport potentials
Raghav Kansal, David Crair, Nghia Nguyen +2
Flow matching (FM) has emerged as a powerful framework for learning dynamic transport maps between two empirical distributions. However, less explored is the setting with intermedi…
An Evaluation of Representation Learning Methods in Particle Physics Foundation Models
Michael Chen, Raghav Kansal, Abhijith Gandrakota +3
We present a systematic evaluation of representation learning objectives for particle physics within a unified framework. Our study employs a shared transformer-based particle-clou…
Particle Cloud Generation with Message Passing Generative Adversarial Networks
Raghav Kansal, Javier Duarte, Hao Su +6
In high energy physics (HEP), jets are collections of correlated particles produced ubiquitously in particle collisions such as those at the CERN Large Hadron Collider (LHC). Machi…