Daniel Whiteson

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 14

Top Topics

Particle Physics

Autoregressive Model

Diffusion Models

Top Venues

Comput. Softw. Big Sci.

Publications

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
The Landscape of Unfolding with Machine Learning. CoRR (2024)
Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson
Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion. CoRR (2024)
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, O. 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, 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, S. A. Ochoa Oregon, J. Oleniacz, J. D. Osborn, C. Paudel, C. Pecar, C. Peng, Gabriel N. Perdue, W. Phelps, M. L. Purschke, H. Rajendran, K. Rajput, Y. Ren, David Francisco Rentería-Estrada, D. Richford, B. J. Roy, D. Roy, A. Saini, Nobuo Sato, T. Satogata, German Sborlini, Malachi Schram, D. Shih, J. Singh, R. Singh, A. Siodmok, J. Stevens, P. Stone, L. Suarez, K. Suresh, A.-N. Tawfik, Fernando Torales Acosta, N. Tran, R. Trotta, F. J. Twagirayezu, R. Tyson, S. Volkova, Anselm Vossen, Eric Walter, Daniel Whiteson, Michael Williams, S. Wu, N. Zachariou, P. Zurita
Artificial Intelligence for the Electron Ion Collider (AI4EIC). Comput. Softw. Big Sci. 8 (1) (2024)
Michael James Fenton, Alexander Shmakov, Hideki Okawa, Yuji Li, Ko-Yang Hsiao, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi
Extended Symmetry Preserving Attention Networks for LHC Analysis. CoRR (2023)
Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson
End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics. NeurIPS (2023)
C. Allaire, R. Ammendola, E.-C. Aschenauer, M. Balandat, Marco Battaglieri, J. C. Bernauer, M. Bondì, N. Branson, Thomas Britton, A. 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, Y. Gao, J. Giroux, N. C. Gunawardhana Waduge, R. Harish, O. 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, M. McEneaney, Diana McSpadden, T. Menzo, T. Miceli, Vinicius Mikuni, R. Montgomery, Benjamin Nachman, R. R. Nair, J. Niestroy, S. A. Ochoa Oregon, J. Oleniacz, J. D. Osborn, C. Paudel, C. Pecar, C. Peng, Gabriel N. Perdue, W. Phelps, M. L. Purschke, K. Rajput, Y. Ren, David Francisco Rentería-Estrada, D. Richford, B. J. Roy, D. Roy, N. Sato, T. Satogata, German Sborlini, Malachi Schram, D. Shih, J. Singh, R. Singh, A. Siodmok, P. Stone, J. Stevens, L. Suarez, K. Suresh, A.-N. Tawfik, Fernando Torales Acosta, N. Tran, R. Trotta, F. J. Twagirayezu, R. Tyson, S. Volkova, A. Vossen, E. Walter, Daniel Whiteson, Michael Williams, S. Wu, N. Zachariou, P. Zurita
Artificial Intelligence for the Electron Ion Collider (AI4EIC). CoRR (2023)
Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson
End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics. CoRR (2023)
Junze Liu, Aishik Ghosh, Dylan Smith, Pierre Baldi, Daniel Whiteson
Generalizing to new calorimeter geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation. CoRR (2023)
Junze Liu, Aishik Ghosh, Dylan Smith, Pierre Baldi, Daniel Whiteson
Geometry-aware Autoregressive Models for Calorimeter Shower Simulations. CoRR (2022)
Phiala Shanahan, Kazuhiro Terao, Daniel Whiteson
Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning. CoRR (2022)
Jack H. Collins, Yifeng Huang, Simon Knapen, Benjamin Nachman, Daniel Whiteson
Machine-Learning Compression for Particle Physics Discoveries. CoRR (2022)
Alexander Shmakov, Michael James Fenton, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi
SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention. CoRR (2021)
Michael James Fenton, Alexander Shmakov, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi
Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networks. CoRR (2020)
Pierre Baldi, Kyle Cranmer, Taylor Faucett, Peter J. Sadowski, Daniel Whiteson
Parameterized Machine Learning for High-Energy Physics. CoRR (2016)
Peter J. Sadowski, Julian Collado, Daniel Whiteson, Pierre Baldi
Deep Learning, Dark Knowledge, and Dark Matter. HEPML@NIPS (2014)
Pierre Baldi, Peter J. Sadowski, Daniel Whiteson
Enhanced Higgs to $τ^+τ^-$ Searches with Deep Learning. CoRR (2014)
Peter J. Sadowski, Daniel Whiteson, Pierre Baldi
Searching for Higgs Boson Decay Modes with Deep Learning. NIPS (2014)
Shimon Whiteson, Daniel Whiteson
Machine learning for event selection in high energy physics. Eng. Appl. Artif. Intell. 22 (8) (2009)
Shimon Whiteson, Daniel Whiteson
Stochastic Optimization for Collision Selection in High Energy Physics. AAAI (2007)