Sandra Hirche
21 papers · 2017–2025 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (38) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Keyword Champion
(5)
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Dynamic Duo
(11)
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Prolific Year · Productive
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Unstoppable · Bronze
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The Questioner
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Century Club · Bronze
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Conference Pioneer
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Keyword Collector
(93)
Top co-authors
Research topics
Machine Learning
(18)
Artificial Intelligence
(13)
Optimization & Theory
(11)
Core AI
(10)
Robotics
(9)
Mathematics & Optimization
(8)
Optimization
(8)
Bayesian & Probabilistic · Machine Learning
(7)
Bayesian & Probabilistic · Artificial Intelligence
(6)
Learning Types
(6)
Systems
(5)
Core Methods
(3)
Application Areas
(2)
Applications
(2)
Capabilities
(2)
Keywords
gaussian process
(10)
gaussian process regression
(5)
uncertainty quantification
(4)
dynamical system
(4)
model uncertainty
(3)
learning-based control
(3)
online learning
(3)
reproducing kernel hilbert space
(2)
uniform error bound
(2)
safety guarantee
(2)
lyapunov stability
(2)
nonlinear system
(2)
koopman operator
(2)
global optimization
(1)
bayesian inference
(1)
stability analysis
(1)
variational inference
(1)
reinforcement learning
(1)
model predictive control
(1)
distributed learning
(1)
Papers
Asynchronous Distributed Gaussian Process Regression
AAAI 2025
Kernel-Based Optimal Control: An Infinitesimal Generator Approach
L4DC 2025
Koopman-Equivariant Gaussian Processes
AISTATS 2025
Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks
AISTATS 2025
Learning Safe Control via On-the-Fly Bandit Exploration
ICML 2025
Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models
L4DC 2025
Computation-Aware Learning for Stable Control with Gaussian Process
RSS 2024
Jacta: A Versatile Planner for Learning Dexterous and Whole-body Manipulation
CoRL 2024
Physically consistent modeling & identification of nonlinear friction with dissipative Gaussian processes
L4DC 2024
Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning
L4DC 2023
Koopman Kernel Regression
NeurIPS 2023
Sharp Calibrated Gaussian Processes
NeurIPS 2023
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications
ICML 2022
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators
L4DC 2022
Gaussian Process-Based Real-Time Learning for Safety Critical Applications
ICML 2021
The Impact of Data on the Stability of Learning-Based Control
L4DC 2021
Localized active learning of Gaussian process state space models
L4DC 2020
Parameter Optimization for Learning-based Control of Control-Affine Systems
L4DC 2020
Smart Forgetting for Safe Online Learning with Gaussian Processes
L4DC 2020
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
NeurIPS 2019
Learning Stable Stochastic Nonlinear Dynamical Systems
ICML 2017