https://www.a-marx.com https://www.a-marx.com/publications https://www.a-marx.com/projects https://www.a-marx.com/people https://www.a-marx.com/courses https://www.a-marx.com/posts https://www.a-marx.com/pages https://www.a-marx.com/cv https://www.a-marx.com/contact_form https://www.a-marx.com/publications/56061-recovering-causal-features-for-instrumental-variable-regression-with-contrastive-learning https://www.a-marx.com/publications/56059-regression-based-estimation-of-causal-effects-in-the-presence-of-selection-bias-and-confounding https://www.a-marx.com/publications/56060-skewness-robust-causal-discovery-in-location-scale-noise-models https://www.a-marx.com/publications/37813-two-is-better-than-one-aligned-representation-pairs-for-anomaly-detection https://www.a-marx.com/publications/52784-a-cautionary-tale-about-neutrally-informative-ai-tools-ahead-of-the-2025-federal-elections-in-germany https://www.a-marx.com/publications/42469-on-the-properties-and-estimation-of-pointwise-mutual-information-profiles https://www.a-marx.com/publications/37812-predicting-risk-for-nocturnal-hypoglycemia-after-physical-activity-in-children-with-type-1-diabetes https://www.a-marx.com/publications/42468-transfer-learning-for-pediatric-glucose-forecasting https://www.a-marx.com/publications/24065-exploiting-causal-graph-priors-with-posterior-sampling-for-reinforcement-learning https://www.a-marx.com/publications/27489-blood-glucose-forecasting-from-temporal-and-static-information-in-children-with-t1d https://www.a-marx.com/publications/25983-effective-bayesian-heteroscedastic-regression-with-deep-neural-networks https://www.a-marx.com/publications/21853-beyond-normal-on-the-evaluation-of-mutual-information-estimators https://www.a-marx.com/publications/25984-the-mixtures-and-the-neural-critics-on-the-pointwise-mutual-information-profiles-of-fine-distributions https://www.a-marx.com/publications/14921-on-the-identifiability-and-estimation-of-causal-location-scale-noise-models https://www.a-marx.com/publications/21180-identifiability-results-for-multimodal-contrastive-learning https://www.a-marx.com/publications/21181-3didentbox-a-toolbox-for-identifiability-benchmarking https://www.a-marx.com/publications/9341-inferring-cause-and-effect-in-the-presence-of-heteroscedastic-noise https://www.a-marx.com/publications/5723-estimating-mutual-information-via-geodesic-knn https://www.a-marx.com/publications/5423-formally-justifying-mdl-based-inference-of-cause-and-effect https://www.a-marx.com/publications/9342-causal-inference-with-heteroscedastic-noise-models https://www.a-marx.com/publications/5427-a-weaker-faithfulness-assumption-based-on-triple-interactions https://www.a-marx.com/publications/5424-estimating-conditional-mutual-information-for-discrete-continuous-mixtures-using-multidimensional-adaptive-histograms https://www.a-marx.com/publications/5428-discovering-fully-oriented-causal-networks https://www.a-marx.com/publications/5430-integrative-analysis-of-epigenetics-data-identifies-gene-specific-regulatory-elements https://www.a-marx.com/publications/5425-information-theoretic-causal-discovery https://www.a-marx.com/publications/5422-identifiability-of-cause-and-effect-using-regularized-regression https://www.a-marx.com/publications/5421-telling-cause-from-effect-by-local-and-global-regression https://www.a-marx.com/publications/5419-testing-conditional-independence-on-discrete-data-using-stochastic-complexity https://www.a-marx.com/publications/5420-approximating-algorithmic-conditional-independence-for-discrete-data https://www.a-marx.com/publications/5418-stochastic-complexity-for-testing-conditional-independence-on-discrete-data https://www.a-marx.com/publications/5415-causal-inference-on-multivariate-and-mixed-type-data https://www.a-marx.com/publications/5414-telling-cause-from-effect-using-mdl-based-local-and-global-regression https://www.a-marx.com/publications/5413-edison-wmw-exact-dynamic-programming-solution-of-the-wilcoxon-mann-whitney-test https://www.a-marx.com/pages/5117-news_arxiv https://www.a-marx.com/pages/5828-teaching