Tobias Sutter

Full Professorship (W3) in Machine Learning Deadline: January 31, 2026

We @uni-konstanz.de are hiring a full professor in machine learning for our MSc program in Social and Economic Data Science: stellen.uni-konstanz.de/jobposting/6...

New print on optimal decision making by exploiting statistical concentration properties of the underlying data generating process …

arxiv.org/pdf/2507.15215

Poster „Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound“

I‘ll be presenting my poster on solving probabilistic verification problems of NNs at ICML today! Meet me at poster E-2302 :)

To be presented at ICML 2025

arxiv.org/pdf/2405.17556

New preprint on optimal offline RL

arxiv.org/pdf/2503.12283

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms When training neural networks with custom objectives, such as ranking losses and shortest-path losses, a common problem is that they are, per se, non-differentiable. A popular approach is to continuou...

I'm excited to share our NeurIPS 2024 paper "Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms" 🤖.
Paper link 📜: arxiv.org/abs/2410.19055