Raghav Kansal

According to our database, Raghav Kansal authored at least 16 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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., December, 2023

FAIR AI models in high energy physics.

Javier M. Duarte, Haoyang Li, Avik Roy, Ruike Zhu, E. A. Huerta, Daniel Diaz, Philip C. Harris, Raghav Kansal, Daniel S. Katz, Ishaan H. Kavoori, Volodymyr V. Kindratenko, Farouk Mokhtar, Mark S. Neubauer, Sang Eon Park, Melissa Quinnan, Roger Rusack, Zhizhen Zhao

Mach. Learn. Sci. Technol., December, 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., November, 2023

Induced Generative Adversarial Particle Transformers.

Anni Li, Venkat Krishnamohan, Raghav Kansal, Rounak Sen, Steven Tsan, Zhaoyu Zhang, Javier M. Duarte

CoRR, 2023

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

Lorentz Group Equivariant Autoencoders.

Zichun Hao, Raghav Kansal, Javier M. Duarte, Nadezda Chernyavskaya

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

Do graph neural networks learn traditional jet substructure?

Farouk Mokhtar, Raghav Kansal, Javier M. Duarte

CoRR, 2022

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

2021

Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance.

Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz, Javier M. Duarte, Sukanya Krishna, Farouk Mokhtar, Jean-Roch Vlimant, Maurizio Pierini

CoRR, 2021

Explaining machine-learned particle-flow reconstruction.

Farouk Mokhtar, Raghav Kansal, Daniel Diaz, Javier M. Duarte, Joosep Pata, Maurizio Pierini, Jean-Roch Vlimant

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, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

CoRR, 2021

A FAIR and AI-ready Higgs Boson Decay Dataset.

Yifan Chen, E. A. Huerta, Javier M. Duarte, Philip C. Harris, Daniel S. Katz, Mark S. Neubauer, Daniel Diaz, Farouk Mokhtar, Raghav Kansal, Sang Eon Park, Volodymyr V. Kindratenko, Zhizhen Zhao, Roger Rusack

CoRR, 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

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

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