Sutter, Tobias

12 publications

NeurIPS 2025 Distributional Adversarial Attacks and Training in Deep Hedging Guangyi He, Tobias Sutter, Lukas Gonon

ICML 2025 Solving Probabilistic Verification Problems of Neural Networks Using Branch and Bound David Boetius, Stefan Leue, Tobias Sutter

NeurIPS 2024 Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms Felix Petersen, Christian Borgelt, Tobias Sutter, Hilde Kuehne, Oliver Deussen, Stefano Ermon

NeurIPS 2024 Randomized Algorithms and PAC Bounds for Inverse Reinforcement Learning in Continuous Spaces Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter, Volkan Cevher, John Lygeros

ICML 2024 Regularized Q-Learning Through Robust Averaging Peter Schmitt-Förster, Tobias Sutter

ICML 2023 A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks David Boetius, Stefan Leue, Tobias Sutter

ICML 2023 End-to-End Learning for Stochastic Optimization: A Bayesian Perspective Yves Rychener, Daniel Kuhn, Tobias Sutter

ICLR 2023 ISAAC Newton: Input-Based Approximate Curvature for Newton's Method Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne, Yuekai Sun, Oliver Deussen

ICML 2021 Distributionally Robust Optimization with Markovian Data Mengmeng Li, Tobias Sutter, Daniel Kuhn

NeurIPS 2021 Robust Generalization Despite Distribution Shift via Minimum Discriminating Information Tobias Sutter, Andreas Krause, Daniel Huhn

JMLR 2019 Generalized Maximum Entropy Estimation Tobias Sutter, David Sutter, Peyman Mohajerin Esfahani, John Lygeros

JMLR 2016 A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes Tobias Sutter, Arnab Ganguly, Heinz Koeppl