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ORCIDRaghav Kansal
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2020 – today
- 2023
[j4]Raghav Kansal
, Carlos Pareja, Zichun Hao, Javier M. Duarte:
JetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physics. J. Open Source Softw. 8(91): 5789 (2023)- [j3]Breno Orzari, Nadezda Chernyavskaya, Raphael Cóbe, Javier M. Duarte, Jefferson F. Coelho, Dimitrios Gunopulos, Raghav Kansal, Maurizio Pierini, Thiago Tomei, Mary Touranakou:
LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows. Mach. Learn. Sci. Technol. 4(4): 45023 (2023) - [j2]Javier M. Duarte, Haoyang Li, Avik Roy, Ruike Zhu, Eliu 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:
FAIR AI models in high energy physics. Mach. Learn. Sci. Technol. 4(4): 45062 (2023) - [i12]Anni Li, Venkat Krishnamohan, Raghav Kansal, Rounak Sen, Steven Tsan, Zhaoyu Zhang, Javier M. Duarte:
Induced Generative Adversarial Particle Transformers. CoRR abs/2312.04757 (2023) - 2022
- [j1]Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant:
Particle-based fast jet simulation at the LHC with variational autoencoders. Mach. Learn. Sci. Technol. 3(3): 35003 (2022) - [d1]Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant:
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders: generator-level and reconstruction-level jets dataset. Zenodo, 2022
- [i11]Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopoulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant:
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders. CoRR abs/2203.00520 (2022) - [i10]Farouk Mokhtar, Raghav Kansal, Javier M. Duarte:
Do graph neural networks learn traditional jet substructure? CoRR abs/2211.09912 (2022) - [i9]Raghav Kansal, Anni Li, Javier M. Duarte, Nadezda Chernyavskaya, Maurizio Pierini, Breno Orzari, Thiago Tomei:
On the Evaluation of Generative Models in High Energy Physics. CoRR abs/2211.10295 (2022) - [i8]Javier M. Duarte, Haoyang Li, Avik Roy, Ruike Zhu, Eliu 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:
FAIR AI Models in High Energy Physics. CoRR abs/2212.05081 (2022) - [i7]Zichun Hao, Raghav Kansal, Javier M. Duarte, Nadezda Chernyavskaya:
Lorentz Group Equivariant Autoencoders. CoRR abs/2212.07347 (2022) - 2021
- [c1]Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. NeurIPS 2021: 23858-23871 - [i6]Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. CoRR abs/2106.11535 (2021) - [i5]Yifan Chen, Eliu 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:
A FAIR and AI-ready Higgs Boson Decay Dataset. CoRR abs/2108.02214 (2021) - [i4]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:
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021) - [i3]Farouk Mokhtar, Raghav Kansal, Daniel Diaz, Javier M. Duarte, Joosep Pata, Maurizio Pierini, Jean-Roch Vlimant:
Explaining machine-learned particle-flow reconstruction. CoRR abs/2111.12840 (2021) - [i2]Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz, Javier M. Duarte, Sukanya Krishna, Farouk Mokhtar, Jean-Roch Vlimant, Maurizio Pierini:
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. CoRR abs/2111.12849 (2021) - 2020
- [i1]Raghav Kansal, Javier M. Duarte, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos:
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. CoRR abs/2012.00173 (2020)
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