Alexander Marx

Postdoctoral Researcher


alexander.marx(at)bsse.ethz.ch


BSSE

ETH Zürich

Incoming Professor at TU Dortmund



Publications


Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning


Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

ICLR, 2024 May


Blood Glucose Forecasting from Temporal and Static Information in Children with T1D


Alexander Marx, Francesco Di Stefano, Heike Leutheuse, Kieran Chin-Cheong, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann Brenner, Julia E. Vogt

Frontiers in Pediatrics, vol. 11, 2023


Effective Bayesian Heteroscedastic Regression with Deep Neural Networks


Alexander Immer, Emanuele Palumbo, Alexander Marx*, Julia E Vogt*

NeurIPS, 2023 Dec


Beyond Normal: On the Evaluation of Mutual Information Estimators


Paweł Czyz, Frederic Grabowski, Julia E Vogt, Niko Beerenwinkel*, Alexander Marx*

NeurIPS, 2023 Dec


The Mixtures and the Neural Critics: On the Pointwise Mutual Information Profiles of Fine Distributions


Paweł Czyz, Frederic Grabowski, Julia E Vogt, Niko Beerenwinkel*, Alexander Marx*

2023 Oct


On the Identifiability and Estimation of Causal Location-Scale Noise Models


Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx

ICML, 2023 Jul


Identifiability Results for Multimodal Contrastive Learning


Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E Vogt

ICLR, 2023 May


3DIdentBox: A Toolbox for Identifiability Benchmarking


Alice Bizeul, Imant Daunhawer, Emanuele Palumbo, Bernhard Schölkopf, Alexander Marx, Julia E Vogt

CleaR (Dataset Track), 2023 Apr


Inferring Cause and Effect in the Presence of Heteroscedastic Noise


Sascha Xu, Osman Mian, Alexander Marx, Jilles Vreeken

ICML, 2022 Jul


Estimating Mutual Information via Geodesic kNN


Alexander Marx, Jonas Fischer

SIAM SDM, 2022 Apr


Formally Justifying MDL-based Inference of Cause and Effect


Alexander Marx, Jilles Vreeken

AAAI Workshop ITCI, 2022 Mar


Causal Inference with Heteroscedastic Noise Models


Sascha Xu, Alexander Marx, Osman Mian, Jilles Vreeken

AAAI Workshop ITCI, 2022 Mar


A Weaker Faithfulness Assumption based on Triple Interactions


Alexander Marx, Arthur Gretton, Joris M. Mooij

UAI, 2021


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


Alexander Marx, Lincen Yang, Matthijs van Leeuwen

SIAM SDM, 2021, pp. 387--395


Discovering Fully Oriented Causal Networks


Osman Mian, Alexander Marx, Jilles Vreeken

AAAI, 2021


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


Identifiability of Cause and Effect using Regularized Regression


Alexander Marx, Jilles Vreeken

KDD, 2019


Telling cause from effect by local and global regression


Alexander Marx, Jilles Vreeken

Knowledge and Information Systems, 2019


Approximating Algorithmic Conditional Independence for Discrete Data


Alexander Marx, Jilles Vreeken

AAAI Symposium WHY, 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

ECMLPKDD, 2018


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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