10 citations · 13 across the 3 of their papers we have counts for
3 papers
hep-ex2024
Fast multi-geometry calorimeter simulation with conditional self-attention variational autoencoders
Dylan Smith, Aishik Ghosh, Junze Liu +2
The simulation of detector response is a vital aspect of data analysis in particle physics, but current Monte Carlo methods are computationally expensive. Machine learning methods,…
physics.ins-det2023★ 10 cited
Generalizing to new geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation
Junze Liu, Aishik Ghosh, Dylan Smith +2
Generation of simulated detector response to collision products is crucial to data analysis in particle physics, but computationally very expensive. One subdetector, the calorimete…
physics.ins-det2022★ 3 cited
Geometry-aware Autoregressive Models for Calorimeter Shower Simulations
Junze Liu, Aishik Ghosh, Dylan Smith +2
Calorimeter shower simulations are often the bottleneck in simulation time for particle physics detectors. A lot of effort is currently spent on optimizing generative architectures…