Feature relevance quantification in explainable AI: A causality problem. - Dominik Janzing; Lenon Minorics; Patrick Blöbaum (CoRR, 2019)

Feature relevance quantification in explainable AI: A causal problem. - Dominik Janzing; Lenon Minorics; Patrick Blöbaum (AISTATS, 2020)

Quantifying causal contribution via structure preserving interventions. - Dominik Janzing; Patrick Blöbaum; Lenon Minorics (CoRR, 2020)

Causal Forecasting: Generalization Bounds for Autoregressive Models. - Leena C. Vankadara; Philipp Michael Faller; Lenon Minorics; Debarghya Ghoshdastidar; Dominik Janzing (CoRR, 2021)

Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. - Lenon Minorics; Ali Caner Türkmen; David Kernert; Patrick Blöbaum; Laurent Callot; Dominik Janzing (AISTATS, 2022)

Causal structure-based root cause analysis of outliers. - Kailash Budhathoki; Lenon Minorics; Patrick Blöbaum; Dominik Janzing (ICML, 2022)

Causal forecasting: generalization bounds for autoregressive models. - Leena Chennuru Vankadara; Philipp Michael Faller; Michaela Hardt; Lenon Minorics; Debarghya Ghoshdastidar; Dominik Janzing (UAI, 2022)

Correcting Confounding via Random Selection of Background Variables. - You-Lin Chen; Lenon Minorics; Dominik Janzing (CoRR, 2022)

Manifold Restricted Interventional Shapley Values. - Muhammad Faaiz Taufiq; Patrick Blöbaum; Lenon Minorics (AISTATS, 2023)

Unsupervised Model Selection for Time Series Anomaly Detection. - Mononito Goswami; Cristian I. Challu; Laurent Callot; Lenon Minorics; Andrey Kan (ICLR, 2023)

Quantifying intrinsic causal contributions via structure preserving interventions. - Dominik Janzing; Patrick Blöbaum; Atalanti-Anastasia Mastakouri; Philipp Michael Faller; Lenon Minorics; Kailash Budhathoki (AISTATS, 2024)

νSAM: Memory-Efficient Sharpness-Aware Minimization via Nuclear Norm Constraints. - Thomas Pethick; Parameswaran Raman; Lenon Minorics; Mingyi Hong 001; Shoham Sabach; Volkan Cevher (Trans. Mach. Learn. Res., 2025)