Alexander Marx

Postdoctoral Researcher


alexander.marx(at)inf.ethz.ch


BSSE

ETH Zürich



Alexander Marx

Postdoctoral Researcher


Contact

Alexander Marx

Postdoctoral Researcher


alexander.marx(at)inf.ethz.ch


BSSE

ETH Zürich




I am a Postdoctoral Researcher in the Computational Biology Group at ETH Zürich, and a member of the ELLIS society and the Swiss Institute for Bioinformatics (SIB). My research focuses on causality, information theory, and representation learning to approach modern challenges in the medical and biological domain. Prior to my current position, I was 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.

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)
  • 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


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