Alexander Marx

Professor


alexander.marx(at)tu-dortmund.de


Department of Statistics

TU Dortmund



Alexander Marx

Professor


Contact

Alexander Marx

Professor


alexander.marx(at)tu-dortmund.de


Department of Statistics

TU Dortmund




I am a professor at TU Dortmund, leading the Causality group at the Research Center for Trustworthy Data Science and Security and the Department of Statistics, and a member of the ELLIS society. My research is at the intersection of causality and machine learning, focusing on causal discovery, causal representation learning, information theory, and Bayesian deep learning. Prior to my current position, I was a Postdoctoral Researcher Computational Biology Group at ETH Zürich, a Postdoc-Fellow at the ETH AI Center and part of the Medical Data Science Group. I did my PhD in the Exploratory Data Analysis group affiliated with the CISPA Helmholtz Center for Information Security and the Max Planck Institute for Informatics.

Job Advertisement

I am actively searching for PhD students and research assistants. Feel free to reach out! More details are provided here.

News

For more updates access the news arxiv.

Activities

Reviewing for Conferences & Journals

  • Reviewer for the Conference on Neural Information Processing Systems (NeurIPS'23 [Top 10% Reviewer Award])
  • Reviewer for the International Conference on Machine Learning (ICML'22,23,24)
  • Reviewer for the International Conference on Artificial Intelligence and Statistics (AISTATS'21,22 [Top 10% Reviewer Award],23[Top 10% Reviewer Award],24)
  • PC Member for the SIAM International Conference on Data Mining (SDM'21)
  • PC Member for the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'21)
  • Reviewer for the Machine Learning for Health Symposium (ML4H'22,23)
  • Reviewed for the journal Data Mining and Knowledge Discovery (DAMI'22)
  • Reviewed for the journal IEEE Access in 2020
  • Reviewer for the IEEE International Symposium on Information Theory (ISIT'19,20)
  • PC Member for the workshops AAAI-ITCI'22 and NeurIPS-TS4H

Invited Talks

Publications


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


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


Paweł Czyz, Frederic Grabowski, Julia E Vogt, Niko Beerenwinkel*, Alexander Marx*

2023 Oct


View all
Share



Follow this website


You need to create an Owlstown account to follow this website.


Sign up

Already an Owlstown member?

Log in