activity
20222026
most citedReconstructing particles in jets using set transformer and hypergraph prediction networks

29 citations · 36 across the 6 of their papers we have counts for

collaborators

7 papers

hep-ph2026

Prompting Particle Physics: Tokenized Multi-modal Foundation Models for Combinatorially Many Tasks

Nilotpal Kakati, Daniel Murnane, Baran Hashemi +5

Reconstruction and simulation at a collider experiment are long chains of specialised algorithms, each tuned to a single step. We explore how one model can serve many of those step…

astro-ph.HE2026

Light Antinuclei Coalescence: Femtoscopic Constraints via Neural-Flow Surrogates

M. Korwieser, L. Fabbietti, B. Hashemi +4

Precise predictions of cosmic-ray antinuclei fluxes, a prime dark matter signature, are limited by the lack of data constraining production rates of antinuclei. We mitigate this bo…

cs.LG2026

BRICKS: Compositional Neural Markov Kernels for Zero-Shot Radiation-Matter Simulation

Richard Hildebrandt, Evangelos Kourlitis, Baran Hashemi +7

We introduce a new strategy for compositional neural surrogates for radiation-matter interactions, a key task spanning domains from particle physics through nuclear and space engin…

hep-ex2024★ 1 cited

HGPflow: Extending Hypergraph Particle Flow to Collider Event Reconstruction

Nilotpal Kakati, Etienne Dreyer, Anna Ivina +4

In high energy physics, the ability to reconstruct particles based on their detector signatures is essential for downstream data analyses. A particle reconstruction algorithm based…

hep-ex2023★ 1 cited

Configurable calorimeter simulation for AI applications

Francesco Armando Di Bello, Anton Charkin-Gorbulin, Kyle Cranmer +9

A configurable calorimeter simulation for AI (COCOA) applications is presented, based on the Geant4 toolkit and interfaced with the Pythia event generator. This open-source project…

hep-ex2022★ 29 cited

Reconstructing particles in jets using set transformer and hypergraph prediction networks

Francesco Armando Di Bello, Etienne Dreyer, Sanmay Ganguly +8

The task of reconstructing particles from low-level detector response data to predict the set of final state particles in collision events represents a set-to-set prediction task r…

hep-ex2022★ 5 cited

Set-Conditional Set Generation for Particle Physics

Francesco Armando Di Bello, Etienne Dreyer, Sanmay Ganguly +6

The simulation of particle physics data is a fundamental but computationally intensive ingredient for physics analysis at the Large Hadron Collider, where observational set-valued…