On the Properties and Estimation of Pointwise Mutual Information Profiles
Pawel Czyz, Frederic Grabowski, Julia E Vogt, Niko Beerenwinkel, Alexander Marx
Transactions on Machine Learning Research, 2025
Predicting Risk for Nocturnal Hypoglycemia after Physical Activity in Children with Type 1 Diabetes
Heike Leutheuser, Marc Bartholet, Alexander Marx, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann, Julia E Vogt
Frontiers in Medicine, vol. 11, Frontiers, 2024
Anomaly Detection by Context Contrasting
Alain Ryser, Thomas M Sutter, Alexander Marx, Julia E Vogt
arXiv preprint arXiv:2405.18848, 2024
Transfer Learning for Pediatric Glucose Forecasting
Alain Ryse, Chuhao Feng, Tobias Scheithauer, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann, Alexander Marx, Julia E. Vogt
Machine Learning for Health Symposium, PMLR, 2024 Dec
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
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
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
Alexander Marx, Lincen Yang, Matthijs van Leeuwen
SIAM SDM, 2021, pp. 387--395
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
Testing Conditional Independence on Discrete Data using Stochastic Complexity
Alexander Marx, Jilles Vreeken
AISTATS, 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
Telling Cause from Effect using MDL-based Local and Global Regression
Alexander Marx, Jilles Vreeken
ICDM, 2017
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