Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance
… the interdependencies among the particles within a jet, for such tasks. Additionally, we develop
a differentiable approximation to the energy mover’s distance via a graph neural network, …
a differentiable approximation to the energy mover’s distance via a graph neural network, …
arXiv: Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance
S Tsan, S Krishna, A Aportela, R Kansal, D Diaz… - 2021 - cds.cern.ch
… the interdependencies among the particles within a jet, for such tasks. Additionally, we develop
a differentiable approximation to the energy mover’s distance via a graph neural network, …
a differentiable approximation to the energy mover’s distance via a graph neural network, …
Differentiable Earth mover's distance for data compression at the high-luminosity LHC
R Shenoy, J Duarte, C Herwig… - Machine Learning …, 2023 - iopscience.iop.org
… differentiable approximation in the training of an autoencoder-… mover's distance for use in
particle reconstruction. The … to approximate the energy mover's distance in a differentiable way …
particle reconstruction. The … to approximate the energy mover's distance in a differentiable way …
LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows
B Orzari, N Chernyavskaya, R Cobe… - Machine Learning …, 2023 - iopscience.iop.org
… variational autoencoder (ConVAE) for the generation of particle… of invertible and differentiable
mappings usually learned by … earth mover's distance (EMD) [47], or 1-Wasserstein distance…
mappings usually learned by … earth mover's distance (EMD) [47], or 1-Wasserstein distance…
Learning geometry-aware joint latent space for simultaneous multimodal shape generation
… We propose a new geometry-aware autoencoder for 3D … , the gradients of the particle loss
are differentiable with respect to … (For interpretation of the colors in the figure(s), the reader is …
are differentiable with respect to … (For interpretation of the colors in the figure(s), the reader is …
[PDF][PDF] 2nd Workshop of Machine Learning for Quantum Technology
… learning approaches available, variational autoencoders … the evolution of the one-particle
density profile. Building on the … Our research showcases the use of Differentiable Quantum …
density profile. Building on the … Our research showcases the use of Differentiable Quantum …
[CITATION][C] Particle graph autoencoders and differentiable, learned energy mover's distance,(arXiv preprint) doi: 10.48550
S Tsan, R Kansal, A Aportela, D Diaz, J Duarte… - arXiv preprint arXiv.2111.12849
[CITATION][C] Particle Graph Autoencoders and Differentiable
S Tsan, R Kansal, A Aportela, D Diaz, J Duarte… - … Energy Mover's Distance …, 2021