About
Stephan Eckstein is a junior professor in the Department of Mathematics at the University of Tübingen and a member of the university's machine learning cluster. His research bridges probability theory and machine learning with particular focus on stochastic optimization and numerical approximation.
Research interests include:
- Optimal transport theory and its computational aspects
- Regularization techniques for high-dimensional problems
- Causal models and probabilistic structures
- Graphical models in machine learning
- Graph neural networks
Recent publications analyze dimensional stability in optimal transport, exponential convergence rates for Sinkhorn algorithms, and causal modeling in financial time series generation.
Contact: stephan.eckstein@uni-tuebingen.de
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