Tilman Plehn

According to our database, Tilman Plehn authored at least 17 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Forecasting Generative Amplification.

Henning Bahl, Sascha Diefenbacher, Nina Elmer, Tilman Plehn, Jonas Spinner

CoRR, September, 2025

Simulation-Prior Independent Neural Unfolding Procedure.

Anja Butter, Theo Heimel, Nathan Huetsch, Michael Kagan, Tilman Plehn

CoRR, July, 2025

Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 1 Pions.

Michele Faucci Giannelli, Gregor Kasieczka, Claudius Krause, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Florian Ernst, Anthony L. Caterini, Federico A. G. Corchia, Jesse C. Cresswell, Etienne Dreyer, Luigi Favaro, Matteo Franchini, Eilam Gross, Shih-Chieh Hsu, Taewoo Kim, Dmitrii Kobylianskii, Marco Letizia, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Ian Pang, Kevin Pedro, Tilman Plehn, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Chase Shimmin, Eli Shlizerman, Shu Li, Nathalie Soybelman, Rui Zhang

Dataset, June, 2025

Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 1 Photons.

Michele Faucci Giannelli, Gregor Kasieczka, Claudius Krause, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Anthony L. Caterini, Federico A. G. Corchia, Jesse C. Cresswell, Etienne Dreyer, Florian Ernst, Luigi Favaro, Matteo Franchini, Eilam Gross, Shih-Chieh Hsu, Taewoo Kim, Dmitrii Kobylianskii, Marco Letizia, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Vinicius Mikuni, Ian Pang, Kevin Pedro, Tilman Plehn, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Chase Shimmin, Eli Shlizerman, Shu Li, Nathalie Soybelman, Rui Zhang

Dataset, June, 2025

Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant.

Jonas Spinner, Luigi Favaro, Peter Lippmann, Sebastian Pitz, Gerrit Gerhartz, Tilman Plehn, Fred A. Hamprecht

CoRR, May, 2025

2024

Extrapolating Jet Radiation with Autoregressive Transformers.

Anja Butter, François Charton, Javier Mariño Villadamigo, Ayodele Ore, Tilman Plehn, Jonas Spinner

CoRR, 2024

Generative Unfolding with Distribution Mapping.

Anja Butter, Sascha Diefenbacher, Nathan Huetsch, Vinicius Mikuni, Benjamin Nachman, Sofia Palacios Schweitzer, Tilman Plehn

CoRR, 2024

A Lorentz-Equivariant Transformer for All of the LHC.

Johann Brehmer, Victor Bresó, Pim de Haan, Tilman Plehn, Huilin Qu, Jonas Spinner, Jesse Thaler

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, 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

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

Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics.

Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Anomalies, Representations, and Self-Supervision.

Barry M. Dillon, Luigi Favaro, Friedrich Feiden, Tanmoy Modak, Tilman Plehn

CoRR, 2023

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, Kai Zhou

Comput. Softw. Big Sci., December, 2022

2021

Generative Networks for Precision Enthusiasts.

Anja Butter, Theo Heimel, Sander Hummerich, Tobias Krebs, Tilman Plehn, Armand Rousselot, Sophia Vent

CoRR, 2021

Better Latent Spaces for Better Autoencoders.

Barry M. Dillon, Tilman Plehn, Christof Sauer, Peter Sorrenson

CoRR, 2021

Understanding Event-Generation Networks via Uncertainties.

Marco Bellagente, Manuel Haußmann, Michel Luchmann, Tilman Plehn

CoRR, 2021

2019

How to GAN away Detector Effects.

Marco Bellagente, Anja Butter, Gregor Kasieczka, Tilman Plehn, Ramon Winterhalder

CoRR, 2019