Daniel Gedon
Postdoctoral Researcher
ELLIS Institute Tübingen ·
Tübingen AI Center · University of Tübingen
About
I am a postdoctoral researcher at the ELLIS Institute Tübingen and the Tübingen AI Center at the University of Tübingen, working with Jakob Macke in the Machine Learning in Science group. I develop probabilistic machine learning methods for scientific discovery, with a focus on simulation-based inference and foundation models for science.
Research Interests
Scientific model discovery
Simulation-based inference
Foundation models for science
LLMs for science
Probabilistic ML
ECG deep learning
Selected Papers
A Probabilistic Framework for LLM-Based Model Discovery
A deep learning ECG model for identification and localization of occlusion myocardial infarction
Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models
No Double Descent in Principal Component Regression: A High-Dimensional Analysis