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Patrick Blöbaum
Patrick Blöbaum
Amazon (AWS)
Verified email at amazon.com
Title
Cited by
Cited by
Year
Feature relevance quantification in explainable AI: A causal problem
D Janzing, L Minorics, P Blöbaum
International Conference on Artificial Intelligence and Statistics, 2907-2916, 2020
3772020
Cause-effect inference by comparing regression errors
P Blöbaum, D Janzing, T Washio, S Shimizu, B Schölkopf
International Conference on Artificial Intelligence and Statistics, 900-909, 2018
902018
Causal structure-based root cause analysis of outliers
K Budhathoki, L Minorics, P Blöbaum, D Janzing
International Conference on Machine Learning, 2357-2369, 2022
62*2022
DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models
P Blöbaum, P Götz, K Budhathoki, AA Mastakouri, D Janzing
Journal of Machine Learning Research 25 (147), 1-7, 2024
512024
Why did the distribution change?
K Budhathoki, D Janzing, P Blöbaum, H Ng
International Conference on Artificial Intelligence and Statistics, 1666-1674, 2021
452021
On Measuring Causal Contributions via do-interventions
Y Jung, S Kasiviswanathan, J Tian, D Janzing, P Blöbaum, E Bareinboim
International Conference on Machine Learning, 10476-10501, 2022
262022
Analysis of cause-effect inference by comparing regression errors
P Blöbaum, D Janzing, T Washio, S Shimizu, B Schölkopf
PeerJ Computer Science 5, e169, 2019
212019
Quantifying intrinsic causal contributions via structure preserving interventions
D Janzing, P Blöbaum, AA Mastakouri, PM Faller, L Minorics, ...
International Conference on Artificial Intelligence and Statistics, 2188-2196, 2024
18*2024
Sequential kernelized independence testing
A Podkopaev, P Blöbaum, S Kasiviswanathan, A Ramdas
International Conference on Machine Learning, 27957-27993, 2023
182023
Interventional and counterfactual inference with diffusion models
P Chao, P Blöbaum, SP Kasiviswanathan
arXiv preprint arXiv:2302.00860 4, 16, 2023
182023
Estimation of interventional effects of features on prediction
P Blöbaum, S Shimizu
IEEE 27th International Workshop on Machine Learning for Signal Processing …, 2017
132017
Manifold restricted interventional shapley values
MF Taufiq, P Blöbaum, L Minorics
International Conference on Artificial Intelligence and Statistics, 5079-5106, 2023
92023
Error asymmetry in causal and anticausal regression
P Blöbaum, T Washio, S Shimizu
Behaviormetrika, 1-22, 2017
92017
Toward Falsifying Causal Graphs Using a Permutation-Based Test
E Eulig, AA Mastakouri, P Blöbaum, M Hardt, D Janzing
arXiv preprint arXiv:2305.09565, 2023
82023
Thompson Sampling with Diffusion Generative Prior
YG Hsieh, SP Kasiviswanathan, B Kveton, P Blöbaum
International Conference on Machine Learning, 13434-13468, 2023
62023
Discriminative and generative models in causal and anticausal settings
P Blöbaum, S Shimizu, T Washio
Advanced Methodologies for Bayesian Networks: Second International Workshop …, 2015
52015
Unsupervised Dimensionality Reduction for Transfer Learning
P Blöbaum, A Schulz, B Hammer
23rd European Symposium on Artificial Neural Networks, Computational …, 2015
52015
Recent advances in semi-parametric methods for causal discovery
S Shimizu, P Blöbaum
Direction Dependence in Statistical Modeling: Methods of Analysis, 111-130, 2020
32020
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
L Minorics, C Turkmen, D Kernert, P Blöbaum, L Callot, D Janzing
International Conference on Artificial Intelligence and Statistics, 10534-10554, 2022
22022
Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
A Dalal, P Blöbaum, S Kasiviswanathan, A Ramdas
arXiv preprint arXiv:2408.09598, 2024
12024
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Articles 1–20