Alexander Marx

Orcid: 0000-0002-1575-824X

Affiliations:
  • CISPA Helmholtz Center for Information Security, Saarbrücken, Germany


According to our database1, Alexander Marx authored at least 24 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2023
The Mixtures and the Neural Critics: On the Pointwise Mutual Information Profiles of Fine Distributions.
CoRR, 2023

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.
CoRR, 2023

Effective Bayesian Heteroscedastic Regression with Deep Neural Networks.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

Identifiability Results for Multimodal Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Estimating Mutual Information via Geodesic <i>k</i>NN.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Inferring Cause and Effect in the Presence of Heteroscedastic Noise.
Proceedings of the International Conference on Machine Learning, 2022

Learning Features via Transformer Networks for Cardiomyocyte Profiling.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021
Information-Theoretic Causal Discovery.
PhD thesis, 2021

Estimating Mutual Information via Geodesic kNN.
CoRR, 2021

Formally Justifying MDL-based Inference of Cause and Effect.
CoRR, 2021

A weaker faithfulness assumption based on triple interactions.
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.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Discovering Fully Oriented Causal Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
Telling cause from effect by local and global regression.
Knowl. Inf. Syst., 2019

Identifiability of Cause and Effect using Regularized Regression.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Testing Conditional Independence on Discrete Data using Stochastic Complexity.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Causal Discovery by Telling Apart Parents and Children.
CoRR, 2018

Causal Inference on Multivariate and Mixed-Type Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

2017
A Forest Vitality and Change Monitoring Tool Based on RapidEye Imagery.
IEEE Geosci. Remote. Sens. Lett., 2017

Causal Inference on Multivariate Mixed-Type Data by Minimum Description Length.
CoRR, 2017

Telling Cause from Effect Using MDL-Based Local and Global Regression.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test.
Genom. Proteom. Bioinform., 2016


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