Alexander Marx


Postdoc Fellow


alexander.marx(at)inf.ethz.ch


ETH AI Center


ETH Zürich



Publications


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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


Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multidimensional Adaptive Histograms


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

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