How to GAN away Detector Effects. - Marco Bellagente; Anja Butter; Gregor Kasieczka; Tilman Plehn; Ramon Winterhalder (CoRR, 2019)

Deep Learning for Physics Research - Martin Erdmann; Jonas Glombitza; Gregor Kasieczka; Uwe Klemradt (WorldScientific, 2021)

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

Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed. - Erik Buhmann; Sascha Diefenbacher; Engin Eren; Frank Gaede; Gregor Kasieczka; Anatolii Korol; Katja Krüger (Comput. Softw. Big Sci., 2021)

Radio Galaxy Classification with wGAN-Supported Augmentation. - Janis Kummer; Lennart Rustige; Florian Griese; Kerstin Borras; Marcus Brüggen; Patrick L. S. Connor; Frank Gaede; Gregor Kasieczka; Peter Schleper (GI-Jahrestagung, 2022)

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)

Data Science and Machine Learning in Education. - Gabriele Benelli; Thomas Y. Chen; Javier M. Duarte; Matthew Feickert; Matthew J. Graham; Lindsey Gray; Dan Hackett; Philip C. Harris; Shih-Chieh Hsu; Gregor Kasieczka; Elham E Khoda; Matthias Komm; et al. (CoRR, 2022)

Feature Selection with Distance Correlation. - Ranit Das; Gregor Kasieczka; David Shih (CoRR, 2022)

Hadrons, better, faster, stronger. - Erik Buhmann; Sascha Diefenbacher; Daniel Hundhausen; Gregor Kasieczka; William Korcari; Engin Eren; Frank Gaede; Katja Krüger; Peter McKeown; Lennart Rustige (Mach. Learn. Sci. Technol., 2022)

Shared Data and Algorithms for Deep Learning in Fundamental Physics. - Lisa Benato; Erik Buhmann; Martin Erdmann; Peter Fackeldey; Jonas Glombitza; Nikolai Hartmann; Gregor Kasieczka; William Korcari; Thomas Kuhr; Jan Steinheimer; Horst Stöcker; Tilman Plehn; et al. (Comput. Softw. Big Sci., 2022)

EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets. - Erik Buhmann; Gregor Kasieczka; Jesse Thaler (CoRR, 2023)

CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation. - Erik Buhmann; Sascha Diefenbacher; Engin Eren; Frank Gaede; Gregor Kasieczka; Anatolii Korol; William Korcari; Katja Krüger; Peter McKeown (CoRR, 2023)

CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation. - Erik Buhmann; Frank Gaede; Gregor Kasieczka; Anatolii Korol; William Korcari; Katja Krüger; Peter McKeown (CoRR, 2023)

EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion. - Erik Buhmann; Cedric Ewen; Darius A. Faroughy; Tobias Golling; Gregor Kasieczka; Matthew Leigh; Guillaume Quétant; John Andrew Raine; Debajyoti Sengupta; David Shih (CoRR, 2023)

Statistical guarantees for stochastic Metropolis-Hastings. - Sebastian Bieringer; Gregor Kasieczka; Maximilian F. Steffen; Mathias Trabs (CoRR, 2023)

Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Information. - Joschka Birk; Erik Buhmann; Cedric Ewen; Gregor Kasieczka; David Shih (CoRR, 2023)

Residual ANODE. - Ranit Das; Gregor Kasieczka; David Shih (CoRR, 2023)

AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization. - Sebastian Bieringer; Gregor Kasieczka; Maximilian F. Steffen; Mathias Trabs (CoRR, 2023)

New angles on fast calorimeter shower simulation. - Sascha Diefenbacher; Engin Eren; Frank Gaede; Gregor Kasieczka; Anatolii Korol; Katja Krüger; Peter McKeown; Lennart Rustige (Mach. Learn. Sci. Technol., 2023)

Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. - Patrick Odagiu; Zhiqiang Que; Javier M. Duarte; Johannes Haller; Gregor Kasieczka; Artur Lobanov; Vladimir Loncar; Wayne Luk; Jennifer Ngadiuba; Maurizio Pierini; Philipp Rincke; Arpita Seksaria; et al. (CoRR, 2024)

Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows. - Thorsten Buss; Frank Gaede; Gregor Kasieczka; Claudius Krause; David Shih (CoRR, 2024)

Universal New Physics Latent Space. - Anna Hallin; Gregor Kasieczka; Sabine Kraml; André Lessa; Louis Moureaux; Tore von Schwartz; David Shih (CoRR, 2024)

Calibrating Bayesian Generative Machine Learning for Bayesiamplification. - Sebastian Bieringer; Sascha Diefenbacher; Gregor Kasieczka; Mathias Trabs (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)

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

OmniJet-α: the first cross-task foundation model for particle physics. - Joschka Birk; Anna Hallin; Gregor Kasieczka (Mach. Learn. Sci. Technol., 2024)

Ultrafast jet classification at the HL-LHC. - Patrick Odagiu; Zhiqiang Que; Javier M. Duarte; Johannes Haller; Gregor Kasieczka; Artur Lobanov; Vladimir Loncar; Wayne Luk; Jennifer Ngadiuba; Maurizio Pierini; Philipp Rincke; Arpita Seksaria; et al. (Mach. Learn. Sci. Technol., 2024)

Aspen Open Jets: a real-world ML-ready dataset for jet physics. - Oz Amram; Luca Anzalone; Joschka Birk; Darius A. Faroughy; Anna Hallin; Gregor Kasieczka; Michael Krämer; Ian Pang; Humberto Reyes-González; David Shih (UHH-FDR, 2024)

Aspen Open Jets: unlocking LHC data for foundation models in particle physics. - Oz Amram; Luca Anzalone; Joschka Birk; Darius A. Faroughy; Anna Hallin; Gregor Kasieczka; Michael Krämer; Ian Pang; Humberto Reyes-González; David Shih (Mach. Learn. Sci. Technol., 2025)

Large Physics Models: Towards a collaborative approach with Large Language Models and Foundation Models. - Kristian Gonzalez Barman; Sascha Caron; Emily Sullivan; Henk W. de Regt; Roberto Ruiz de Austri; Mieke Boon; Michael Färber 001; Stefan Fröse; Faegheh Hasibi; Andreas Ipp; Rukshak Kapoor; Gregor Kasieczka; et al. (CoRR, 2025)

OmniJet-αC: Learning point cloud calorimeter simulations using generative transformers. - Joschka Birk; Frank Gaede; Anna Hallin; Gregor Kasieczka; Martina Mozzanica; Henning Rose (CoRR, 2025)

CaloHadronic: a diffusion model for the generation of hadronic showers. - Thorsten Buss; Frank Gaede; Gregor Kasieczka; Anatolii Korol; Katja Krüger; Peter McKeown; Martina Mozzanica (CoRR, 2025)