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Raghav Kansal
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2020 – today
- 2024
- [i13]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, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang:
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. CoRR abs/2410.21611 (2024) - 2023
- [j4]Raghav Kansal
, Carlos Pareja
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
LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows. Mach. Learn. Sci. Technol. 4(4): 45023 (2023) - [j2]Javier M. Duarte
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
Particle-based fast jet simulation at the LHC with variational autoencoders. Mach. Learn. Sci. Technol. 3(3): 35003 (2022) - [d1]Mary Touranakou
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
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
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021) - [i3]Farouk Mokhtar, Raghav Kansal, Daniel Diaz
Explaining machine-learned particle-flow reconstruction. CoRR abs/2111.12840 (2021) - [i2]Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. CoRR abs/2111.12849 (2021) - 2020
- [i1]Raghav Kansal, Javier M. Duarte
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. CoRR abs/2012.00173 (2020)
Coauthor Index
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