Alexander Marx

According to our database, Alexander Marx authored at least 26 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Anomaly Detection by Context Contrasting.

Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt

CoRR, 2024

Imaging spectroscopy for bark beetle detection in Norway spruce and the relevance of the red-edge spectral range.

Alexander Marx, Anne Clasen, Johannes May, Simon König, Birgit Kleinschmit, Michael Förster

Int. J. Appl. Earth Obs. Geoinformation, 2024

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

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

Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx

CoRR, 2023

Effective Bayesian Heteroscedastic Regression with Deep Neural Networks.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond Normal: On the Evaluation of Mutual Information Estimators.

Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

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

Proceedings of the International Conference on Machine Learning, 2023

Identifiability Results for Multimodal Contrastive Learning.

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Estimating Mutual Information via Geodesic <i>k</i>NN.

Alexander Marx, Jonas Fischer

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

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, 2022

Learning Features via Transformer Networks for Cardiomyocyte Profiling.

Jan Plier, Matthias Zisler, Jennifer Furkel, Maximilian Knoll, Alexander Marx, Alena Fischer, Kai Polsterer, Mathias H. Konstandin, Stefania Petra

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021

Information-Theoretic Causal Discovery.

Alexander Marx

PhD thesis, 2021

Estimating Mutual Information via Geodesic kNN.

Alexander Marx, Jonas Fischer

CoRR, 2021

Formally Justifying MDL-based Inference of Cause and Effect.

Alexander Marx, Jilles Vreeken

CoRR, 2021

A weaker faithfulness assumption based on triple interactions.

Alexander Marx, Arthur Gretton, Joris M. Mooij

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms.

Alexander Marx, Lincen Yang, Matthijs van Leeuwen

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Discovering Fully Oriented Causal Networks.

Osman Mian, Alexander Marx, Jilles Vreeken

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Telling cause from effect by local and global regression.

Alexander Marx, Jilles Vreeken

Knowl. Inf. Syst., 2019

Identifiability of Cause and Effect using Regularized Regression.

Alexander Marx, Jilles Vreeken

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Testing Conditional Independence on Discrete Data using Stochastic Complexity.

Alexander Marx, Jilles Vreeken

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Causal Discovery by Telling Apart Parents and Children.

Alexander Marx, Jilles Vreeken

CoRR, 2018

Causal Inference on Multivariate and Mixed-Type Data.

Alexander Marx, Jilles Vreeken

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

2017

A Forest Vitality and Change Monitoring Tool Based on RapidEye Imagery.

Alexander Marx, Gideon Okpoti Tetteh

IEEE Geosci. Remote. Sens. Lett., 2017

Causal Inference on Multivariate Mixed-Type Data by Minimum Description Length.

Alexander Marx, Jilles Vreeken

CoRR, 2017

Telling Cause from Effect Using MDL-Based Local and Global Regression.

Alexander Marx, Jilles Vreeken

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016

EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test.

Alexander Marx, Christina Backes, Eckart Meese, Hans-Peter Lenhof, Andreas Keller

Genom. Proteom. Bioinform., 2016