Hirche, Sandra

22 publications

AAAI 2025 Asynchronous Distributed Gaussian Process Regression Zewen Yang, Xiaobing Dai, Sandra Hirche

L4DC 2025 Kernel-Based Optimal Control: An Infinitesimal Generator Approach Petar Bevanda, Nicolas Hoischen, Tobias Wittmann, Jan Brudigam, Sandra Hirche, Boris Houska

AISTATS 2025 Koopman-Equivariant Gaussian Processes Petar Bevanda, Max Beier, Alexandre Capone, Stefan Georg Sosnowski, Sandra Hirche, Armin Lederer

AISTATS 2025 Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche

ICML 2025 Learning Safe Control via On-the-Fly Bandit Exploration Alexandre Capone, Ryan Kazuo Cosner, Aaron Ames, Sandra Hirche

L4DC 2025 Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen, Jan Brudigam, Xuehua Xiao, Stefan Sosnowski, Sandra Hirche

ICMLW 2024 Gaussian Process-Based Representation Learning via Timeseries Symmetries Petar Bevanda, Max Beier, Armin Lederer, Alexandre Capone, Stefan Georg Sosnowski, Sandra Hirche

CoRL 2024 Jacta: A Versatile Planner for Learning Dexterous and Whole-Body Manipulation Jan Bruedigam, Ali Adeeb Abbas, Maks Sorokin, Kuan Fang, Brandon Hung, Maya Guru, Stefan Georg Sosnowski, Jiuguang Wang, Sandra Hirche, Simon Le Cleac’h

ICMLW 2024 Learning Diffeomorphic Lyapunov Functions from Data Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche

L4DC 2024 Physically Consistent Modeling & Identification of Nonlinear Friction with Dissipative Gaussian Processes Rui Dai, Giulio Evangelisti, Sandra Hirche

L4DC 2023 Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning Xiaobing Dai, Armin Lederer, Zewen Yang, Sandra Hirche

NeurIPS 2023 Koopman Kernel Regression Petar Bevanda, Max Beier, Armin Lederer, Stefan Sosnowski, Eyke Hüllermeier, Sandra Hirche

NeurIPS 2023 Sharp Calibrated Gaussian Processes Alexandre Capone, Sandra Hirche, Geoff Pleiss

ICML 2022 Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications Alexandre Capone, Armin Lederer, Sandra Hirche

L4DC 2022 Structure-Preserving Learning Using Gaussian Processes and Variational Integrators Jan Brüdigam, Martin Schuck, Alexandre Capone, Stefan Sosnowski, Sandra Hirche

ICML 2021 Gaussian Process-Based Real-Time Learning for Safety Critical Applications Armin Lederer, Alejandro J Ordóñez Conejo, Korbinian A Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche

L4DC 2021 The Impact of Data on the Stability of Learning-Based Control Armin Lederer, Alexandre Capone, Thomas Beckers, Jonas Umlauft, Sandra Hirche

L4DC 2020 Localized Active Learning of Gaussian Process State Space Models Alexandre Capone, Gerrit Noske, Jonas Umlauft, Thomas Beckers, Armin Lederer, Sandra Hirche

L4DC 2020 Parameter Optimization for Learning-Based Control of Control-Affine Systems Armin Lederer, Alexandre Capone, Sandra Hirche

L4DC 2020 Smart Forgetting for Safe Online Learning with Gaussian Processes Jonas Umlauft, Thomas Beckers, Alexandre Capone, Armin Lederer, Sandra Hirche

NeurIPS 2019 Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control Armin Lederer, Jonas Umlauft, Sandra Hirche

ICML 2017 Learning Stable Stochastic Nonlinear Dynamical Systems Jonas Umlauft, Sandra Hirche