Matthias Schott

According to our database, Matthias Schott authored at least 9 papers between 2022 and 2026.

Collaborative distances:

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

2026

Transfer Learning Across Fast- and Full-Simulation Domains in High-Energy Physics.

Matthias Schott, Lucie Flek

CoRR, May, 2026

Uncovering Hidden Systematics in Neural Network Models for High Energy Physics.

Lucie Flek, Philipp Alexander Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Christopher Wiebusch, Ulrich Willemsen

CoRR, May, 2026

Learning Minimal-Deviation Corrections for Multi-Dimensional Mismodelling in HEP Simulations.

Matthias Schott, Lucie Flek

CoRR, May, 2026

Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications.

Philip Bechtle, Lucie Flek, Philipp Alexander Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Christopher Wiebusch, Ulrich Willemsen

CoRR, March, 2026

2025

Enforcing Fundamental Relations via Adversarial Attacks on Input Parameter Correlations.

Lucie Flek, Philipp Alexander Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Christopher Wiebusch

Comput. Softw. Big Sci., December, 2025

MiniFool - Physics-Constraint-Aware Minimizer-Based Adversarial Attacks in Deep Neural Networks.

Lucie Flek, Oliver Janik, Philipp Alexander Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Matthias Thiesmeyer, Christopher Wiebusch, Ulrich Willemsen

CoRR, November, 2025

Introduction to the Usage of Open Data from the Large Hadron Collider for Computer Scientists in the Context of Machine Learning.

Timo Saala, Matthias Schott

CoRR, January, 2025

Colliding with Adversaries: A Challenge on Robust Learning in High Energy Physics at ECML PKDD 2025.

Timo Saala, Lucie Flek, Akbar Karimi, Philipp Alexander Jung, Alexander Schmidt, Philipp Soldin, Dimitris Stefanopoulos, Andreas Voskou, Ulrich Willemsen, Christopher Wiebusch, Matthias Schott

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025

2022

Pile-up mitigation using attention.

Benedikt Maier, S. M. Narayanan, G. de Castro, Maxim Goncharov, Christoph Paus, Matthias Schott

Mach. Learn. Sci. Technol., 2022