Alexander Marx

37 papers A* 9A 4Journal 20Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	A Cautionary Tale About "Neutrally" Informative AI Tools Ahead of the 2025 Federal Elections in Germany. xAI (5) Ina Dormuth, Sven Franke, Marlies Hafer, Tim Katzke, Alexander Marx, Emmanuel Müller, Daniel Neider, Markus Pauly, Jérôme Rutinowski
2025	J	`jnl`	A Cautionary Tale About "Neutrally" Informative AI Tools Ahead of the 2025 Federal Elections in Germany. CoRR Ina Dormuth, Sven Franke, Marlies Hafer, Tim Katzke, Alexander Marx, Emmanuel Müller, Daniel Neider, Markus Pauly, Jérôme Rutinowski
2025	J	`jnl`	On the Properties and Estimation of Pointwise Mutual Information Profiles. Trans. Mach. Learn. Res. Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx
2025	J	`jnl`	Regression-Based Estimation of Causal Effects in the Presence of Selection Bias and Confounding. CoRR Marlies Hafer, Alexander Marx
2025	J	`jnl`	Skewness-Robust Causal Discovery in Location-Scale Noise Models. CoRR Daniel Klippert, Alexander Marx
2025	J	`jnl`	Two Is Better Than One: Aligned Representation Pairs for Anomaly Detection. Trans. Mach. Learn. Res. Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt
2024	J	`jnl`	Anomaly Detection by Context Contrasting. CoRR Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt
2024	A*	`conf`	Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning. ICLR Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi
2024	—	`conf`	Transfer Learning for Pediatric Glucose Forecasting. ML4H@NeurIPS Alain Ryser, Chuhao Feng, Tobias Scheithauer, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann, Alexander Marx, Julia E. Vogt
2023	A*	`conf`	Beyond Normal: On the Evaluation of Mutual Information Estimators. NeurIPS Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx
2023	J	`jnl`	Beyond Normal: On the Evaluation of Mutual Information Estimators. CoRR Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx
2023	A*	`conf`	Effective Bayesian Heteroscedastic Regression with Deep Neural Networks. NeurIPS Alexander Immer, Emanuele Palumbo, Alexander Marx, Julia E. Vogt
2023	J	`jnl`	Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning. CoRR Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi
2023	A*	`conf`	Identifiability Results for Multimodal Contrastive Learning. ICLR Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E. Vogt
2023	J	`jnl`	Identifiability Results for Multimodal Contrastive Learning. CoRR Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E. Vogt
2023	A*	`conf`	On the Identifiability and Estimation of Causal Location-Scale Noise Models. ICML Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
2023	J	`jnl`	The Mixtures and the Neural Critics: On the Pointwise Mutual Information Profiles of Fine Distributions. CoRR Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx
2022	A	`conf`	Estimating Mutual Information via Geodesic SDM Alexander Marx, Jonas Fischer
2022	A*	`conf`	Inferring Cause and Effect in the Presence of Heteroscedastic Noise. ICML Sascha Xu, Osman Mian, Alexander Marx, Jilles Vreeken
2022	J	`jnl`	On the Identifiability and Estimation of Causal Location-Scale Noise Models. CoRR Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
2021	A	`conf`	A weaker faithfulness assumption based on triple interactions. UAI Alexander Marx, Arthur Gretton, Joris M. Mooij
2021	A*	`conf`	Discovering Fully Oriented Causal Networks. AAAI Osman Mian, Alexander Marx, Jilles Vreeken
2021	A	`conf`	Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms. SDM Alexander Marx, Lincen Yang, Matthijs van Leeuwen
2021	J	`jnl`	Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms. CoRR Alexander Marx, Lincen Yang, Matthijs van Leeuwen
2021	J	`jnl`	Estimating Mutual Information via Geodesic kNN. CoRR Alexander Marx, Jonas Fischer
2021	J	`jnl`	Formally Justifying MDL-based Inference of Cause and Effect. CoRR Alexander Marx, Jilles Vreeken
2021	—	`—`	Information-Theoretic Causal Discovery. Alexander Marx
2020	J	`jnl`	A Weaker Faithfulness Assumption based on Triple Interactions. CoRR Alexander Marx, Arthur Gretton, Joris M. Mooij
2019	A*	`conf`	Identifiability of Cause and Effect using Regularized Regression. KDD Alexander Marx, Jilles Vreeken
2019	J	`jnl`	Telling cause from effect by local and global regression. Knowl. Inf. Syst. Alexander Marx, Jilles Vreeken
2019	A	`conf`	Testing Conditional Independence on Discrete Data using Stochastic Complexity. AISTATS Alexander Marx, Jilles Vreeken
2019	J	`jnl`	Testing Conditional Independence on Discrete Data using Stochastic Complexity. CoRR Alexander Marx, Jilles Vreeken
2018	J	`jnl`	Causal Discovery by Telling Apart Parents and Children. CoRR Alexander Marx, Jilles Vreeken
2018	—	`conf`	Causal Inference on Multivariate and Mixed-Type Data. ECML/PKDD (2) Alexander Marx, Jilles Vreeken
2017	J	`jnl`	Causal Inference on Multivariate Mixed-Type Data by Minimum Description Length. CoRR Alexander Marx, Jilles Vreeken
2017	A*	`conf`	Telling Cause from Effect Using MDL-Based Local and Global Regression. ICDM Alexander Marx, Jilles Vreeken
2016	J	`jnl`	EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test. Genom. Proteom. Bioinform. Alexander Marx, Christina Backes, Eckart Meese, Hans-Peter Lenhof, Andreas Keller