Sascha Diefenbacher

According to our database, Sascha Diefenbacher authored at least 17 papers between 2021 and 2026.

Collaborative distances:

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

2026

Generative Models and Statistical Validation.

Sascha Diefenbacher, Sofia Palacios Schweitzer, Gregor Kasieczka

CoRR, May, 2026

FAIR Universe Weak Lensing ML Uncertainty Challenge: Handling Uncertainties and Distribution Shifts for Precision Cosmology.

Biwei Dai, Po-Wen Chang, Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Ibrahim Elsharkawy, Steven Farrell, Isabelle Guyon, Christopher J. Harris, Elham E Khoda, Benjamin Nachman, David Rousseau, Uros Seljak, Ihsan Ullah, Yulei Zhang

CoRR, April, 2026

2025

Agents of Discovery.

Sascha Diefenbacher, Anna Hallin, Gregor Kasieczka, Michael Krämer, Anne Lauscher, Tim Lukas

CoRR, September, 2025

Forecasting Generative Amplification.

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

CoRR, September, 2025

FAIR Universe - HiggsML Uncertainty Challenge Public Dataset.

Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Po-Wen Chang, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Steven Farrell, Aishik Ghosh, Isabelle Guyon, Christopher J. Harris, Shih-Chieh Hsu, Elham E Khoda, Benjamin Nachman, Peter Nugent, David Rousseau, Ben Thorne, Ihsan Ullah, Yulei Zhang

Dataset, April, 2025

Discriminative versus generative approaches to simulation-based inference.

Benjamin Sluijter, Sascha Diefenbacher, Wahid Bhimji, Benjamin Nachman

Mach. Learn. Sci. Technol., 2025

FAIR Universe HiggsML Uncertainty Dataset and Competition.

Wahid Bhimji, Ragansu Chakkappai, Po-Wen Chang, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Ibrahim Elsharkawy, Steven Farrell, Aishik Ghosh, Cristina Giordano, Isabelle Guyon, Chris Harris, Yota Hashizume, Shih-Chieh Hsu, Elham E Khoda, Claudius Krause, Ang Li, Benjamin Nachman, David Rousseau, Robert Schöfbeck, Maryam Shooshtari, Dennis Schwarz, Ihsan Ullah, Daohan Wang, Yulei Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Calibrating Bayesian generative machine learning for Bayesiamplification.

Sebastian Bieringer, Sascha Diefenbacher, Gregor Kasieczka, Mathias Trabs

Mach. Learn. Sci. Technol., 2024

Generative Unfolding with Distribution Mapping.

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

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

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, Rémy Lyscar, Alexandre Michon, Benjamin Nachman, Peter Nugent, Mathis Reymond, David Rousseau, Benjamin Sluijter, Benjamin Thorne, Ihsan Ullah, Yulei 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

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., September, 2023

Improving Generative Model-based Unfolding with Schrödinger Bridges.

Sascha Diefenbacher, Guan-Horng Liu, Vinicius Mikuni, Benjamin Nachman, Weili Nie

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

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

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