3 papers
cs.LG2026
Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications
Philip Bechtle, Lucie Flek, Philipp Alexander Jung +7
In High Energy Physics, as in many other fields of science, the application of machine learning techniques has been crucial in advancing our understanding of fundamental phenomena.…
cs.LG2025
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
Deep learning techniques have evolved rapidly in recent years, significantly impacting various scientific fields, including experimental particle physics. To effectively leverage t…
cs.LG2025
Enforcing Fundamental Relations via Adversarial Attacks on Input Parameter Correlations
Timo Saala, Lucie Flek, Alexander Jung +5
Correlations between input parameters play a crucial role in many scientific classification tasks, since these are often related to fundamental laws of nature. For example, in high…