Tobias Sutter
11 papers · 2016–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π§ Keyword Pioneer π£ Hot Topic Early Bird π Renaissance Researcher (5)
π
Conference Polyglot
(4)
π
Academic Marathon
(9)
π
Cross-Pollinator
(10)
π
Century Club
(11)
Conferences
ICML (5)
NIPS (3)
JMLR (2)
ICLR (1)
Top co-authors
Keywords
distributionally robust optimization
(3)
stochastic optimization
(2)
bayesian inference
(2)
probabilistic modeling
(1)
convex optimization
(1)
markov decision process
(1)
variational inference
(1)
loss function optimization
(1)
sample complexity
(1)
inverse reinforcement learning
(1)
formal methods
(1)
empirical risk minimization
(1)
dynamic programming
(1)
optimal control
(1)
diffusion process
(1)
decision making
(1)
gradient descent
(1)
parameter inference
(1)
markov chain
(1)
maximum entropy
(1)
Papers
Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
ICML 2025
Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms
NIPS 2024
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
NIPS 2024
Regularized Q-learning through Robust Averaging
ICML 2024
ISAAC Newton: Input-based Approximate Curvature for Newton's Method
ICLR 2023
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
ICML 2023
End-to-End Learning for Stochastic Optimization: A Bayesian Perspective
ICML 2023
Robust Generalization despite Distribution Shift via Minimum Discriminating Information
NIPS 2021
Distributionally Robust Optimization with Markovian Data
ICML 2021
Generalized Maximum Entropy Estimation
JMLR 2019
A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes
JMLR 2016