Stochastic Optimization for Collision Selection in High Energy Physics. - Shimon Whiteson; Daniel Whiteson (AAAI, 2007)

Machine learning for event selection in high energy physics. - Shimon Whiteson; Daniel Whiteson (Eng. Appl. Artif. Intell., 2009)

Deep Learning, Dark Knowledge, and Dark Matter. - Peter J. Sadowski; Julian Collado; Daniel Whiteson; Pierre Baldi (HEPML@NIPS, 2014)

Searching for Higgs Boson Decay Modes with Deep Learning. - Peter J. Sadowski; Daniel Whiteson; Pierre Baldi (NIPS, 2014)

Enhanced Higgs to $τ^+τ^-$ Searches with Deep Learning. - Pierre Baldi; Peter J. Sadowski; Daniel Whiteson (CoRR, 2014)

HIGGS. - Daniel Whiteson (UCI Machine Learning Repository, 2014)

SUSY. - Daniel Whiteson (UCI Machine Learning Repository, 2014)

Parameterized Machine Learning for High-Energy Physics. - Pierre Baldi; Kyle Cranmer; Taylor Faucett; Peter J. Sadowski; Daniel Whiteson (CoRR, 2016)

HEPMASS. - Daniel Whiteson (UCI Machine Learning Repository, 2016)

Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networks. - Michael James Fenton; Alexander Shmakov; Ta-Wei Ho; Shih-Chieh Hsu; Daniel Whiteson; Pierre Baldi (CoRR, 2020)

SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention. - Alexander Shmakov; Michael James Fenton; Ta-Wei Ho; Shih-Chieh Hsu; Daniel Whiteson; Pierre Baldi (CoRR, 2021)

Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning. - Phiala E. Shanahan; Kazuhiro Terao; Daniel Whiteson (CoRR, 2022)

Machine-Learning Compression for Particle Physics Discoveries. - Jack H. Collins; Yifeng Huang; Simon Knapen; Benjamin Nachman; Daniel Whiteson (CoRR, 2022)

Geometry-aware Autoregressive Models for Calorimeter Shower Simulations. - Junze Liu; Aishik Ghosh; Dylan Smith; Pierre Baldi; Daniel Whiteson (CoRR, 2022)

End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics. - Alexander Shmakov; Kevin Greif; Michael James Fenton; Aishik Ghosh; Pierre Baldi; Daniel Whiteson (NeurIPS, 2023)

Generalizing to new calorimeter geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation. - Junze Liu; Aishik Ghosh; Dylan Smith; Pierre Baldi; Daniel Whiteson (CoRR, 2023)

Artificial Intelligence for the Electron Ion Collider (AI4EIC). - 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; et al. (CoRR, 2023)

Extended Symmetry Preserving Attention Networks for LHC Analysis. - Michael James Fenton; Alexander Shmakov; Hideki Okawa; Yuji Li; Ko-Yang Hsiao; Shih-Chieh Hsu; Daniel Whiteson; Pierre Baldi (CoRR, 2023)

Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion. - Alexander Shmakov; Kevin Greif; Michael James Fenton; Aishik Ghosh; Pierre Baldi; Daniel Whiteson (CoRR, 2024)

The Landscape of Unfolding with Machine Learning. - 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 (CoRR, 2024)

Reconstruction of boosted and resolved multi-Higgs-boson events with symmetry-preserving attention networks. - Haoyang Li; Marko Stamenkovic; Alexander Shmakov; Michael Fenton; Darius Shih-Chieh Chao; Kaitlyn Maiya White; Caden Mikkelsen; Jovan Mitic; Cristina Mantilla Suarez; Melissa Quinnan; Greg Landsberg; Harvey B. Newman; et al. (CoRR, 2024)

Learning Broken Symmetries with Approximate Invariance. - Seth Nabat; Aishik Ghosh; Edmund Witkowski; Gregor Kasieczka; Daniel Whiteson (CoRR, 2024)

Artificial Intelligence for the Electron Ion Collider (AI4EIC). - 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; et al. (Comput. Softw. Big Sci., 2024)

Towards AI-assisted Neutrino Flavor Theory Design. - Jason Benjamin Baretz; Max Fieg; Vijay Ganesh 001; Aishik Ghosh; V. Knapp-Perez; Jake Rudolph; Daniel Whiteson (CoRR, 2025)