Patrick Blöbaum

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 30

Top Topics

Diffusion Model

Unsupervised Dimensionality Reduction

Causal Inference

Feature Relevance

Top Venues

Publications

Michaela Hardt, William Roy Orchard, Patrick Blöbaum, Elke Kirschbaum, Shiva Prasad Kasiviswanathan
The PetShop Dataset - Finding Causes of Performance Issues across Microservices. CLeaR (2024)
Francesco Montagna, Philipp Michael Faller, Patrick Blöbaum, Elke Kirschbaum, Francesco Locatello
Score matching through the roof: linear, nonlinear, and latent variables causal discovery. CoRR (2024)
Nastaran Okati, Sergio Hernan Garrido Mejia, William Roy Orchard, Patrick Blöbaum, Dominik Janzing
Root Cause Analysis of Outliers with Missing Structural Knowledge. CoRR (2024)
Dominik Janzing, Patrick Blöbaum, Atalanti-Anastasia Mastakouri, Philipp Michael Faller, Lenon Minorics, Kailash Budhathoki
Quantifying intrinsic causal contributions via structure preserving interventions. AISTATS (2024)
Michaela Hardt, William Orchard, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Elke Kirschbaum
The PetShop Dataset - Finding Causes of Performance Issues across Microservices. CoRR (2023)
Muhammad Faaiz Taufiq, Patrick Blöbaum, Lenon Minorics
Manifold Restricted Interventional Shapley Values. CoRR (2023)
Aleksandr Podkopaev, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
Sequential Kernelized Independence Testing. ICML (2023)
Michael Oesterle, Patrick Blöbaum, Atalanti-Anastasia Mastakouri, Elke Kirschbaum
Beyond Single-Feature Importance with ICECREAM. CoRR (2023)
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum
Thompson Sampling with Diffusion Generative Prior. CoRR (2023)
Elias Eulig, Atalanti-Anastasia Mastakouri, Patrick Blöbaum, Michaela Hardt, Dominik Janzing
Toward Falsifying Causal Graphs Using a Permutation-Based Test. CoRR (2023)
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum
Thompson Sampling with Diffusion Generative Prior. ICML (2023)
Patrick Chao, Patrick Blöbaum, Shiva Prasad Kasiviswanathan
Interventional and Counterfactual Inference with Diffusion Models. CoRR (2023)
Muhammad Faaiz Taufiq, Patrick Blöbaum, Lenon Minorics
Manifold Restricted Interventional Shapley Values. AISTATS (2023)
Kailash Budhathoki, Lenon Minorics, Patrick Blöbaum, Dominik Janzing
Causal structure-based root cause analysis of outliers. ICML (2022)
Yonghan Jung, Shiva Kasiviswanathan, Jin Tian, Dominik Janzing, Patrick Blöbaum, Elias Bareinboim
On Measuring Causal Contributions via do-interventions. ICML (2022)
Lenon Minorics, Ali Caner Türkmen, David Kernert, Patrick Blöbaum, Laurent Callot, Dominik Janzing
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. AISTATS (2022)
Aleksandr Podkopaev, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
Sequential Kernelized Independence Testing. CoRR (2022)
Patrick Blöbaum, Peter Götz, Kailash Budhathoki, Atalanti-Anastasia Mastakouri, Dominik Janzing
DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models. CoRR (2022)
Kailash Budhathoki, Dominik Janzing, Patrick Blöbaum, Hoiyi Ng
Why did the distribution change? AISTATS (2021)
Kailash Budhathoki, Dominik Janzing, Patrick Blöbaum, Hoiyi Ng
Why did the distribution change? CoRR (2021)
Dominik Janzing, Lenon Minorics, Patrick Blöbaum
Feature relevance quantification in explainable AI: A causal problem. AISTATS (2020)
Dominik Janzing, Patrick Blöbaum, Lenon Minorics
Quantifying causal contribution via structure preserving interventions. CoRR (2020)
Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
Analysis of cause-effect inference by comparing regression errors. PeerJ Comput. Sci. 5 (2019)
Dominik Janzing, Lenon Minorics, Patrick Blöbaum
Feature relevance quantification in explainable AI: A causality problem. CoRR (2019)
Dominik Janzing, Kailash Budhathoki, Lenon Minorics, Patrick Blöbaum
Causal structure based root cause analysis of outliers. CoRR (2019)
Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
Analysis of Cause-Effect Inference via Regression Errors. CoRR (2018)
Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
Cause-Effect Inference by Comparing Regression Errors. AISTATS (2018)
Patrick Blöbaum, Shohei Shimizu, Takashi Washio
A novel principle for causal inference in data with small error variance. ESANN (2017)
Patrick Blöbaum, Shohei Shimizu
Estimation of interventional effects of features on prediction. MLSP (2017)
Patrick Blöbaum, Takashi Washio, Shohei Shimizu
Error Asymmetry in Causal and Anticausal Regression. CoRR (2016)
Patrick Blöbaum, Alexander Schulz, Barbara Hammer
Unsupervised Dimensionality Reduction for Transfer Learning. ESANN (2015)
Patrick Blöbaum, Shohei Shimizu, Takashi Washio
Discriminative and Generative Models in Causal and Anticausal Settings. AMBN@JSAI-isAI (2015)