Superposition Coding Is Almost Always Optimal for the Poisson Broadcast Channel. - Hyeji Kim; Benjamin Nachman; Abbas El Gamal (IEEE Trans. Inf. Theory, 2016)

Controlling Physical Attributes in GAN-Accelerated Simulation of Electromagnetic Calorimeters. - Luke de Oliveira; Michela Paganini; Benjamin Nachman (CoRR, 2017)

CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. - Michela Paganini; Luke de Oliveira; Benjamin Nachman (CoRR, 2017)

Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis. - Luke de Oliveira; Michela Paganini; Benjamin Nachman (Comput. Softw. Big Sci., 2017)

AI Safety for High Energy Physics. - Benjamin Nachman; Chase Shimmin (CoRR, 2019)

A Living Review of Machine Learning for Particle Physics. - Matthew Feickert; Benjamin Nachman (CoRR, 2021)

Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution. - Anders Andreassen; Patrick T. Komiske; Eric M. Metodiev; Benjamin Nachman; Adi Suresh; Jesse Thaler (CoRR, 2021)

Latent Space Refinement for Deep Generative Models. - Ramon Winterhalder; Marco Bellagente; Benjamin Nachman (CoRR, 2021)

New Methods and Datasets for Group Anomaly Detection From Fundamental Physics. - Gregor Kasieczka; Benjamin Nachman; David Shih (CoRR, 2021)

A Cautionary Tale of Decorrelating Theory Uncertainties. - Aishik Ghosh; Benjamin Nachman (CoRR, 2021)

Online-compatible Unsupervised Non-resonant Anomaly Detection. - Vinicius Mikuni; Benjamin Nachman; David Shih (CoRR, 2021)

Learning from learning machines: a new generation of AI technology to meet the needs of science. - 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; et al. (CoRR, 2021)

New directions for surrogate models and differentiable programming for High Energy Physics detector simulation. - Andreas Adelmann; Walter Hopkins; Evangelos Kourlitis; Michael Kagan; Gregor Kasieczka; Claudius Krause; David Shih; Vinicius Mikuni; Benjamin Nachman; Kevin Pedro; Daniel Winklehner (CoRR, 2022)

Exploring the Universality of Hadronic Jet Classification. - Kingman Cheung; Yi-Lun Chung; Shih-Chieh Hsu; Benjamin Nachman (CoRR, 2022)

Score-based Generative Models for Calorimeter Shower Simulation. - Vinicius Mikuni; Benjamin Nachman (CoRR, 2022)

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

Resonant Anomaly Detection with Multiple Reference Datasets. - Mayee F. Chen; Benjamin Nachman; Frederic Sala (CoRR, 2022)

When, Where, and How to Open Data: a Personal Perspective. - Benjamin Nachman (Comput. Softw. Big Sci., 2022)

Initial-State Dependent Optimization of Controlled Gate Operations with Quantum Computer. - Wonho Jang; Koji Terashi; Masahiko Saito; Christian W. Bauer; Benjamin Nachman; Yutaro Iiyama; Ryunosuke Okubo; Ryu Sawada (Quantum, 2022)

Weakly-Supervised Anomaly Detection in the Milky Way. - Mariel Pettee; Sowmya Thanvantri; Benjamin Nachman; David Shih; Matthew R. Buckley; Jack H. Collins (CoRR, 2023)

High-dimensional and Permutation Invariant Anomaly Detection. - Vinicius Mikuni; Benjamin Nachman (CoRR, 2023)

Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulation. - Fernando Torales Acosta; Vinicius Mikuni; Benjamin Nachman; Miguel Arratia; Bishnu Karki; Ryan Milton; Piyush Karande; Aaron Angerami (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)

Improving Generative Model-based Unfolding with Schrödinger Bridges. - Sascha Diefenbacher; Guan-Horng Liu; Vinicius Mikuni; Benjamin Nachman; Weili Nie (CoRR, 2023)

Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation. - Tobias Golling; Samuel Klein; Radha Mastandrea; Benjamin Nachman; John Andrew Raine (CoRR, 2023)

The Optimal use of Segmentation for Sampling Calorimeters. - Fernando Torales Acosta; Bishnu Karki; Piyush Karande; Aaron Angerami; Miguel Arratia; Kenneth Barish; Ryan Milton; Sebastián Morán; Benjamin Nachman; Anshuman Sinha (CoRR, 2023)

Designing Observables for Measurements with Deep Learning. - Owen Long; Benjamin Nachman (CoRR, 2023)

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)

FAIR Universe HiggsML Uncertainty Challenge Competition. - 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; et al. (CoRR, 2024)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - 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; et al. (CoRR, 2024)

Generative Unfolding with Distribution Mapping. - Anja Butter; Sascha Diefenbacher; Nathan Huetsch; Vinicius Mikuni; Benjamin Nachman; Sofia Palacios Schweitzer; Tilman Plehn (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)

Discriminative versus Generative Approaches to Simulation-based Inference. - Benjamin Sluijter; Sascha Diefenbacher; Wahid Bhimji; Benjamin Nachman (CoRR, 2025)

Generator Based Inference (GBI). - Chi Lung Cheng; Ranit Das; Runze Li; Radha Mastandrea; Vinicius Mikuni; Benjamin Nachman; David Shih; Gup Singh (CoRR, 2025)