Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. - Raghav Kansal; Javier M. Duarte; Breno Orzari; Thiago Tomei; Maurizio Pierini; Mary Touranakou; Jean-Roch Vlimant; Dimitrios Gunopoulos (CoRR, 2020)

Particle Cloud Generation with Message Passing Generative Adversarial Networks. - Raghav Kansal; Javier M. Duarte; Hao Su; Breno Orzari; Thiago Tomei; Maurizio Pierini; Mary Touranakou; Jean-Roch Vlimant; Dimitrios Gunopulos (NeurIPS, 2021)

Particle Cloud Generation with Message Passing Generative Adversarial Networks. - Raghav Kansal; Javier M. Duarte; Hao Su; Breno Orzari; Thiago Tomei; Maurizio Pierini; Mary Touranakou; Jean-Roch Vlimant; Dimitrios Gunopoulos (CoRR, 2021)

A FAIR and AI-ready Higgs Boson Decay Dataset. - Yifan Chen; Eliu A. Huerta; Javier M. Duarte; Philip C. Harris; Daniel S. Katz; Mark S. Neubauer; Daniel Diaz 003; Farouk Mokhtar; Raghav Kansal; Sang Eon Park; Volodymyr V. Kindratenko; Zhizhen Zhao 001; et al. (CoRR, 2021)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (CoRR, 2021)

Explaining machine-learned particle-flow reconstruction. - Farouk Mokhtar; Raghav Kansal; Daniel Diaz 003; Javier M. Duarte; Joosep Pata; Maurizio Pierini; Jean-Roch Vlimant (CoRR, 2021)

Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. - Steven Tsan; Raghav Kansal; Anthony Aportela; Daniel Diaz 003; Javier M. Duarte; Sukanya Krishna; Farouk Mokhtar; Jean-Roch Vlimant; Maurizio Pierini (CoRR, 2021)

Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders. - Mary Touranakou; Nadezda Chernyavskaya; Javier M. Duarte; Dimitrios Gunopoulos; Raghav Kansal; Breno Orzari; Maurizio Pierini; Thiago Tomei; Jean-Roch Vlimant (CoRR, 2022)

Do graph neural networks learn traditional jet substructure? - Farouk Mokhtar; Raghav Kansal; Javier M. Duarte (CoRR, 2022)

On the Evaluation of Generative Models in High Energy Physics. - Raghav Kansal; Anni Li; Javier M. Duarte; Nadezda Chernyavskaya; Maurizio Pierini; Breno Orzari; Thiago Tomei (CoRR, 2022)

Lorentz Group Equivariant Autoencoders. - Zichun Hao; Raghav Kansal; Javier M. Duarte; Nadezda Chernyavskaya (CoRR, 2022)

Particle-based fast jet simulation at the LHC with variational autoencoders. - Mary Touranakou; Nadezda Chernyavskaya; Javier M. Duarte; Dimitrios Gunopulos; Raghav Kansal; Breno Orzari; Maurizio Pierini; Thiago Tomei; Jean-Roch Vlimant (Mach. Learn. Sci. Technol., 2022)

Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders: generator-level and reconstruction-level jets dataset. - Mary Touranakou; Nadezda Chernyavskaya; Javier M. Duarte; Dimitrios Gunopulos; Raghav Kansal; Breno Orzari; Maurizio Pierini; Thiago Tomei; Jean-Roch Vlimant (Zenodo, 2022)

Induced Generative Adversarial Particle Transformers. - Anni Li; Venkat Krishnamohan; Raghav Kansal; Rounak Sen; Steven Tsan; Zhaoyu Zhang; Javier M. Duarte (CoRR, 2023)

JetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physics. - Raghav Kansal; Carlos Pareja; Zichun Hao; Javier M. Duarte (J. Open Source Softw., 2023)

FAIR AI models in high energy physics. - Javier M. Duarte; Haoyang Li; Avik Roy; Ruike Zhu; Eliu A. Huerta; Daniel Diaz 003; Philip C. Harris; Raghav Kansal; Daniel S. Katz; Ishaan H. Kavoori; Volodymyr V. Kindratenko; Farouk Mokhtar; et al. (Mach. Learn. Sci. Technol., 2023)

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows. - Breno Orzari; Nadezda Chernyavskaya; Raphael Cóbe; Javier M. Duarte; Jefferson F. Coelho; Dimitrios Gunopulos; Raghav Kansal; Maurizio Pierini; Thiago Tomei; Mary Touranakou (Mach. Learn. Sci. Technol., 2023)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - Claudius Krause; Michele Faucci Giannelli; Gregor Kasieczka; Benjamin Nachman; Dalila Salamani; David Shih; Anna Zaborowska; Oz Amram; Kerstin Borras; Matthew R. Buckley; Erik Buhmann; Thorsten Buss; et al. (CoRR, 2024)

Learning Symmetry-Independent Jet Representations via Jet-Based Joint Embedding Predictive Architecture. - Subash Katel; Haoyang Li; Zihan Zhao; Raghav Kansal; Farouk Mokhtar; Javier M. Duarte (CoRR, 2024)