Inferring Cause and Effect in the Presence of Heteroscedastic Noise
Sascha Xu, Osman Mian, Alexander Marx, Jilles Vreeken
Proceedings of the International Conference on Machine Learning, PMLR, 2022 Jul
Estimating Mutual Information via Geodesic kNN
Alexander Marx, Jonas Fischer
Proceedings of the SIAM International Conference on Data Mining, SIAM, 2022 Apr
Formally Justifying MDL-based Inference of Cause and Effect
Alexander Marx, Jilles Vreeken
Proceedings of the AAAI Workshop on Information Theoretic Causal Inference and Discovery, 2022 Mar
Causal Inference with Heteroscedastic Noise Models
Sascha Xu, Alexander Marx, Osman Mian, Jilles Vreeken
Proceedings of the AAAI Workshop on Information Theoretic Causal Inference and Discovery, 2022 Mar
A Weaker Faithfulness Assumption based on Triple Interactions
Alexander Marx, Arthur Gretton, Joris M. Mooij
Proceedings of the Conference on Uncertainty in Artificial Intelligence, AUAI, 2021
Alexander Marx, Lincen Yang, Matthijs van Leeuwen
Proceedings of the SIAM International Conference on Data Mining, SIAM, 2021, pp. 387--395
Discovering Fully Oriented Causal Networks
Osman Mian, Alexander Marx, Jilles Vreeken
Proceedings of the AAAI Conference on Artificial Intelligence, AAAI, 2021, pp. 8975--8982
Integrative analysis of epigenetics data identifies gene-specific regulatory elements
Florian Schmidt, Alexander Marx, Nina Baumgarten, Marie Hebel, Martin Wegner, Manuel Kaulich, Matthias S Leisegang, Ralf P Brandes, Jonathan Göke, Jilles Vreeken, Marcel H Schulz
Nucleic Acids Research, 2021 Sep
Information-Theoretic Causal Discovery
Alexander Marx
Saarländische Universitäts-und Landesbibliothek, 2021 Jul
Telling cause from effect by local and global regression
Alexander Marx, Jilles Vreeken
Knowledge and Information Systems, vol. 60, 2019, pp. 1277--1305
Testing Conditional Independence on Discrete Data using Stochastic Complexity
Alexander Marx, Jilles Vreeken
Proceedings of the International Conference on Artificial Intelligence and Statistics, PMLR, 2019, pp. 496--505
Identifiability of Cause and Effect using Regularized Regression
Alexander Marx, Jilles Vreeken
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, 2019, pp. 852--861
Approximating Algorithmic Conditional Independence for Discrete Data
Alexander Marx, Jilles Vreeken
First AAAI Spring Symposium Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI, Stanford, 2019
Stochastic Complexity for Testing Conditional Independence on Discrete Data
Alexander Marx, Jilles Vreeken
NeurIPS Workshop on Causal Learning, 2018
Causal Inference on Multivariate and Mixed-Type Data
Alexander Marx, Jilles Vreeken
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Data, Springer, IEEE, 2018, pp. 655-671
Telling Cause from Effect using MDL-based Local and Global Regression
Alexander Marx, Jilles Vreeken
Proceedings of the IEEE International Conference on Data Mining, IEEE, 2017, pp. 307--316
EDISON-WMW: Exact Dynamic Programming Solution of the Wilcoxon-Mann-Whitney Test
Alexander Marx, Christina Backes, Eckart Meese, Hans-Peter Lenhof, Andreas Keller
Genomics, Proteomics & Bioinformatics, vol. 14, Elsevier, 2016, pp. 55--61