Benjamin Nachman

40 papers B 1Journal 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	EveNet: A Foundation Model for Particle Collision Data Analysis. CoRR Ting-Hsiang Hsu, Bai-Hong Zhou, Qibin Liu, Yue Xu, Shu Li, George Wei-Shu Hou, Benjamin Nachman, Shih-Chieh Hsu, Vinicius Mikuni, Yuan-Tang Chou, Yulei Zhang
2026	J	`jnl`	Generalizable Foundation Models for Calorimetry via Mixtures-of-Experts and Parameter Efficient Fine Tuning. CoRR Carlos Cardona-Giraldo, Cristiano Fanelli, James Giroux, Cole Granger, Benjamin Nachman, Gerald Sabin
2025	J	`jnl`	Discriminative versus Generative Approaches to Simulation-based Inference. CoRR Benjamin Sluijter, Sascha Diefenbacher, Wahid Bhimji, Benjamin Nachman
2025	J	`jnl`	Discriminative versus generative approaches to simulation-based inference. Mach. Learn. Sci. Technol. Benjamin Sluijter, Sascha Diefenbacher, Wahid Bhimji, Benjamin Nachman
2025	J	`jnl`	Generator Based Inference (GBI). CoRR Chi Lung Cheng, Ranit Das, Runze Li, Radha Mastandrea, Vinicius Mikuni, Benjamin Nachman, David Shih, Gup Singh
2025	J	`jnl`	SEAL - A Symmetry EncourAging Loss for High Energy Physics. CoRR Pradyun Hebbar, Thandikire Madula, Vinicius Mikuni, Benjamin Nachman, Nadav Outmezguine, Inbar Savoray
2024	J	`jnl`	Artificial Intelligence for the Electron Ion Collider (AI4EIC). Comput. Softw. Big Sci. C. Allaire, R. Ammendola, E.-C. Aschenauer, M. Balandat, Marco Battaglieri, J. C. Bernauer, M. Bondì, N. Branson, T. Britton, Anja Butter, I. Chahrour, P. Chatagnon, Evaristo Cisbani, E. W. Cline, S. Dash, C. T. Dean, W. Deconinck, A. Deshpande, Markus Diefenthaler, R. Ent, Cristiano Fanelli, M. Finger, E. Fol, S. Furletov, Y. Gao, James Giroux, N. C. Gunawardhana Waduge, Omar Hassan, P. L. Hegde, Roger José Hernández-Pinto, Astrid N. Hiller Blin, Tanja Horn, J. Huang, A. Jalotra, D. Jayakodige, B. Joo, M. Junaid, N. Kalantarians, Piyush Karande, B. Kriesten, R. Kunnawalkam Elayavalli, Y. Li, Meifeng Lin, Frank Liu, S. Liuti, G. Matousek, Matthew McEneaney, Diana McSpadden, T. Menzo, T. Miceli, Vinicius Mikuni, R. Montgomery, Benjamin Nachman, R. R. Nair, J. Niestroy, Salvador A. Ochoa-Oregon, J. Oleniacz, J. D. Osborn, Churamani Paudel, Connor Pecar, C. Peng, Gabriel N. Perdue, W. Phelps, Martin L. Purschke, H. Rajendran, Kishansingh Rajput, Y. Ren, David Francisco Rentería-Estrada, D. Richford, B. J. Roy, D. Roy, A. Saini, Nobuo Sato, T. Satogata, German Sborlini, Malachi Schram, David Shih, J. Singh, R. Singh, Andrzej Siódmok, J. Stevens, P. Stone, L. Suarez, K. Suresh, Abdel Nasser Tawfik, Fernando Torales Acosta, N. Tran, R. Trotta, F. J. Twagirayezu, Richard Tyson, S. Volkova, Anselm Vossen, Eric Walter, Daniel Whiteson, Michael Williams, S. Wu, N. Zachariou, P. Zurita
2024	J	`jnl`	CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. CoRR 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
2024	J	`jnl`	FAIR Universe HiggsML Uncertainty Challenge Competition. CoRR Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Steven Farrell, Aishik Ghosh, Isabelle Guyon, Chris Harris, Shih-Chieh Hsu, Elham E Khoda, Rémy Lyscar, Alexandre Michon, Benjamin Nachman, Peter Nugent, Mathis Reymond, David Rousseau, Benjamin Sluijter, Benjamin Thorne, Ihsan Ullah, Yulei Zhang
2024	J	`jnl`	Generative Unfolding with Distribution Mapping. CoRR Anja Butter, Sascha Diefenbacher, Nathan Huetsch, Vinicius Mikuni, Benjamin Nachman, Sofia Palacios Schweitzer, Tilman Plehn
2024	J	`jnl`	The Landscape of Unfolding with Machine Learning. CoRR Nathan Huetsch, Javier Mariño Villadamigo, Alexander Shmakov, Sascha Diefenbacher, Vinicius Mikuni, Theo Heimel, Michael James Fenton, Kevin Greif, Benjamin Nachman, Daniel Whiteson, Anja Butter, Tilman Plehn
2023	J	`jnl`	Artificial Intelligence for the Electron Ion Collider (AI4EIC). CoRR C. Allaire, R. Ammendola, E.-C. Aschenauer, M. Balandat, Marco Battaglieri, J. C. Bernauer, M. Bondì, N. Branson, Thomas Britton, Anja Butter, I. Chahrour, P. Chatagnon, Evaristo Cisbani, E. W. Cline, S. Dash, C. T. Dean, W. Deconinck, A. Deshpande, Markus Diefenthaler, R. Ent, Cristiano Fanelli, M. Finger, M. Finger Jr., E. Fol, S. Furletov, Yuan Gao, James Giroux, N. C. Gunawardhana Waduge, R. Harish, Omar Hassan, P. L. Hegde, Roger José Hernández-Pinto, Astrid N. Hiller Blin, Tanja Horn, J. Huang, D. Jayakodige, B. Joo, M. Junaid, Piyush Karande, B. Kriesten, R. Kunnawalkam Elayavalli, M. Lin, Frank Liu, S. Liuti, G. Matousek, Matthew McEneaney, Diana McSpadden, T. Menzo, T. Miceli, Vinicius Mikuni, R. Montgomery, Benjamin Nachman, R. R. Nair, J. Niestroy, Salvador A. Ochoa-Oregon, J. Oleniacz, J. D. Osborn, Churamani Paudel, Connor Pecar, C. Peng, Gabriel N. Perdue, W. Phelps, Martin L. Purschke, Kishansingh Rajput, Y. Ren, David Francisco Rentería-Estrada, D. Richford, B. J. Roy, D. Roy, Nobuo Sato, T. Satogata, German Sborlini, Malachi Schram, David Shih, J. Singh, R. Singh, Andrzej Siódmok, P. Stone, J. Stevens, L. Suarez, K. Suresh, Abdel Nasser Tawfik, Fernando Torales Acosta, N. Tran, R. Trotta, F. J. Twagirayezu, Richard Tyson, S. Volkova, Anselm Vossen, Eric Walter, Daniel Whiteson, Michael Williams, S. Wu, N. Zachariou, P. Zurita
2023	J	`jnl`	Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulation. CoRR Fernando Torales Acosta, Vinicius Mikuni, Benjamin Nachman, Miguel Arratia, Bishnu Karki, Ryan Milton, Piyush Karande, Aaron Angerami
2023	J	`jnl`	Designing Observables for Measurements with Deep Learning. CoRR Owen Long, Benjamin Nachman
2023	J	`jnl`	Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation. CoRR Tobias Golling, Samuel Klein, Radha Mastandrea, Benjamin Nachman, John Andrew Raine
2023	J	`jnl`	High-dimensional and Permutation Invariant Anomaly Detection. CoRR Vinicius Mikuni, Benjamin Nachman
2023	J	`jnl`	Improving Generative Model-based Unfolding with Schrödinger Bridges. CoRR Sascha Diefenbacher, Guan-Horng Liu, Vinicius Mikuni, Benjamin Nachman, Weili Nie
2023	J	`jnl`	The Optimal use of Segmentation for Sampling Calorimeters. CoRR Fernando Torales Acosta, Bishnu Karki, Piyush Karande, Aaron Angerami, Miguel Arratia, Kenneth Barish, Ryan Milton, Sebastián Morán, Benjamin Nachman, Anshuman Sinha
2023	J	`jnl`	Weakly-Supervised Anomaly Detection in the Milky Way. CoRR Mariel Pettee, Sowmya Thanvantri, Benjamin Nachman, David Shih, Matthew R. Buckley, Jack H. Collins
2022	J	`jnl`	Exploring the Universality of Hadronic Jet Classification. CoRR Kingman Cheung, Yi-Lun Chung, Shih-Chieh Hsu, Benjamin Nachman
2022	J	`jnl`	Initial-State Dependent Optimization of Controlled Gate Operations with Quantum Computer. Quantum Wonho Jang, Koji Terashi, Masahiko Saito, Christian W. Bauer, Benjamin Nachman, Yutaro Iiyama, Ryunosuke Okubo, Ryu Sawada
2022	J	`jnl`	Machine-Learning Compression for Particle Physics Discoveries. CoRR Jack H. Collins, Yifeng Huang, Simon Knapen, Benjamin Nachman, Daniel Whiteson
2022	J	`jnl`	New directions for surrogate models and differentiable programming for High Energy Physics detector simulation. CoRR Andreas Adelmann, Walter Hopkins, Evangelos Kourlitis, Michael Kagan, Gregor Kasieczka, Claudius Krause, David Shih, Vinicius Mikuni, Benjamin Nachman, Kevin Pedro, Daniel Winklehner
2022	J	`jnl`	Resonant Anomaly Detection with Multiple Reference Datasets. CoRR Mayee F. Chen, Benjamin Nachman, Frederic Sala
2022	J	`jnl`	Score-based Generative Models for Calorimeter Shower Simulation. CoRR Vinicius Mikuni, Benjamin Nachman
2022	J	`jnl`	When, Where, and How to Open Data: a Personal Perspective. Comput. Softw. Big Sci. Benjamin Nachman
2021	J	`jnl`	A Cautionary Tale of Decorrelating Theory Uncertainties. CoRR Aishik Ghosh, Benjamin Nachman
2021	J	`jnl`	A Living Review of Machine Learning for Particle Physics. CoRR Matthew Feickert, Benjamin Nachman
2021	J	`jnl`	Latent Space Refinement for Deep Generative Models. CoRR Ramon Winterhalder, Marco Bellagente, Benjamin Nachman
2021	J	`jnl`	Learning from learning machines: a new generation of AI technology to meet the needs of science. CoRR Luca Pion-Tonachini, Kristofer E. Bouchard, Héctor García Martín, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko M. Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel B. Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus H. Zwart, Neeraj Kumar, Amy Justice, Claire J. Tomlin, Daniel A. Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Kenneth Kreutz-Delgado, Michael W. Mahoney, James B. Brown
2021	J	`jnl`	New Methods and Datasets for Group Anomaly Detection From Fundamental Physics. CoRR Gregor Kasieczka, Benjamin Nachman, David Shih
2021	J	`jnl`	Online-compatible Unsupervised Non-resonant Anomaly Detection. CoRR Vinicius Mikuni, Benjamin Nachman, David Shih
2021	J	`jnl`	Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution. CoRR Anders Andreassen, Patrick T. Komiske, Eric M. Metodiev, Benjamin Nachman, Adi Suresh, Jesse Thaler
2019	J	`jnl`	AI Safety for High Energy Physics. CoRR Benjamin Nachman, Chase Shimmin
2017	J	`jnl`	CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. CoRR Michela Paganini, Luke de Oliveira, Benjamin Nachman
2017	J	`jnl`	Controlling Physical Attributes in GAN-Accelerated Simulation of Electromagnetic Calorimeters. CoRR Luke de Oliveira, Michela Paganini, Benjamin Nachman
2017	J	`jnl`	Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis. Comput. Softw. Big Sci. Luke de Oliveira, Michela Paganini, Benjamin Nachman
2016	J	`jnl`	Superposition Coding Is Almost Always Optimal for the Poisson Broadcast Channel. IEEE Trans. Inf. Theory Hyeji Kim, Benjamin Nachman, Abbas El Gamal
2015	J	`jnl`	Superposition Coding is Almost Always Optimal for the Poisson Broadcast Channel. CoRR Hyeji Kim, Benjamin Nachman, Abbas El Gamal
2015	B	`conf`	Superposition coding is almost always optimal for the Poisson broadcast channel. ISIT Hyeji Kim, Benjamin Nachman, Abbas El Gamal