Patrick Blbaum
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
13
Venues
4
Active years
2015–2025
Best venue rank
A*
Where they publish
Papers
13 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AAAI | Toward Falsifying Causal Graphs Using a Permutation-Based Test. | Elias Eulig, Atalanti-Anastasia Mastakouri, Patrick Blbaum, Michaela Hardt, Dominik Janzing |
| 2024 | AISTATS | Quantifying intrinsic causal contributions via structure preserving interventions. | Dominik Janzing, Patrick Blbaum, Atalanti-Anastasia Mastakouri, Philipp Michael Faller, Lenon Minorics, Kailash Budhathoki |
| 2023 | AISTATS | Manifold Restricted Interventional Shapley Values. | Muhammad Faaiz Taufiq, Patrick Blbaum, Lenon Minorics |
| 2023 | ICML | Thompson Sampling with Diffusion Generative Prior. | Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blbaum |
| 2023 | ICML | Sequential Kernelized Independence Testing. | Aleksandr Podkopaev, Patrick Blbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas |
| 2022 | AISTATS | Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. | Lenon Minorics, Ali Caner Trkmen, David Kernert, Patrick Blbaum, Laurent Callot, Dominik Janzing |
| 2022 | ICML | Causal structure-based root cause analysis of outliers. | Kailash Budhathoki, Lenon Minorics, Patrick Blbaum, Dominik Janzing |
| 2022 | ICML | On Measuring Causal Contributions via do-interventions. | Yonghan Jung, Shiva Prasad Kasiviswanathan, Jin Tian, Dominik Janzing, Patrick Blbaum, Elias Bareinboim |
| 2021 | AISTATS | Why did the distribution change? | Kailash Budhathoki, Dominik Janzing, Patrick Blbaum, Hoiyi Ng |
| 2020 | AISTATS | Feature relevance quantification in explainable AI: A causal problem. | Dominik Janzing, Lenon Minorics, Patrick Blbaum |
| 2018 | AISTATS | Cause-Effect Inference by Comparing Regression Errors. | Patrick Blbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schlkopf |
| 2017 | ESANN | A novel principle for causal inference in data with small error variance. | Patrick Blbaum, Shohei Shimizu, Takashi Washio |
| 2015 | ESANN | Unsupervised Dimensionality Reduction for Transfer Learning. | Patrick Blbaum, Alexander Schulz, Barbara Hammer |