Philipp Michael Faller

According to our database, Philipp Michael Faller authored at least 9 papers between 2020 and 2025.

Collaborative distances:

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

2025

On Different Notions of Redundancy in Conditional-Independence-Based Discovery of Graphical Models.

Philipp Michael Faller, Dominik Janzing

CoRR, February, 2025

Cross-validating causal discovery via Leave-One-Variable-Out.

Daniela Schkoda, Philipp Michael Faller, Dominik Janzing, Patrick Blöbaum

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

Score matching through the roof: linear, nonlinear, and latent variables causal discovery.

Francesco Montagna, Philipp Michael Faller, Patrick Blöbaum, Elke Kirschbaum, Francesco Locatello

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

2024

Quantifying intrinsic causal contributions via structure preserving interventions.

Dominik Janzing, Patrick Blöbaum, Atalanti-Anastasia Mastakouri, Philipp Michael Faller, Lenon Minorics, Kailash Budhathoki

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Self-Compatibility: Evaluating Causal Discovery without Ground Truth.

Philipp Michael Faller, Leena C. Vankadara, Atalanti-Anastasia Mastakouri, Francesco Locatello, Dominik Janzing

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Reinterpreting causal discovery as the task of predicting unobserved joint statistics.

Dominik Janzing, Philipp Michael Faller, Leena Chennuru Vankadara

CoRR, 2023

2022

Causal forecasting: generalization bounds for autoregressive models.

Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Causal Forecasting: Generalization Bounds for Autoregressive Models.

Leena C. Vankadara, Philipp Michael Faller, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing

CoRR, 2021

2020

Batch-wise Regularization of Deep Neural Networks for Interpretability.

Nadia Burkart, Philipp Michael Faller, Elisabeth Peinsipp, Marco F. Huber

Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2020