Alexandre Capone

I'm a postdoctoral research scientist at Carnegie Mellon University with Jeff Schneider. I'm interested in various topics from machine learning and control theory. These include reinforcement learning, uncertainty quantification, Bayesian optimization and safe control. I apply my research to autonomous driving, nuclear fusion, and other robotics-related topics.

I did my PhD at the Technical University of Munich, where I was advised by Sandra Hirche. I was also a visiting researcher in 2022 at Caltech with Aaron Ames

Email  /  CV  /  Scholar  /  Linkedin  /  Github

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Publications

For an up-to-date list of my publications, check out my Google scholar profile.
Online Constraint Tightening in Stochastic Model Predictive Control: A Regression Approach
Alexandre Capone, Tim Brüdigam, Sandra Hirche
IEEE Transactions on Automatic Control 2024
arXiv / pdf
Sharp Calibrated Gaussian Processes
Alexandre Capone, Sandra Hirche, Geoff Pleiss
NeurIPS 2023
arXiv / pdf
Learning-based prescribed-time safety for control of unknown systems with control barrier functions
Tzu-Yuan Huang, Sihua Zhang, Xiaobing Dai, Alexandre Capone, Velimir Todorovski, Stefan Sosnowski, and Sandra Hirche.
IEEE Control Systems Letters 2024
arXiv / pdf
Gaussian process uniform error bounds with unknown hyperparameters for safety-critical applications
Alexandre Capone, Armin Lederer, Sandra Hirche
ICML 2022
arXiv / pdf
Backstepping tracking control using Gaussian processes with event-triggered online learning
Junjie Jiao, Alexandre Capone, Sandra Hirche
IEEE Control Systems Letters 2022
pdf
Data selection for multi-task learning under dynamic constraints
Alexandre Capone, Armin Lederer, Jonas Umlauft, Sandra Hirche
IEEE Control Systems Letters 2021
arXiv / pdf
How training data impacts performance in learning-based control
Armin Lederer, Alexandre Capone, Jonas Umlauft, Sandra Hirche
IEEE Control Systems Letters 2021
arXiv / pdf
Backstepping for partially unknown nonlinear systems using Gaussian processes
Alexandre Capone, Sandra Hirche
IEEE Control Systems Letters 2019
pdf
Computation-aware learning for stable control with Gaussian process
Wenhan Cao, Alexandre Capone, Rishabh Yadav, Sandra Hirche, Wei Pan
RSS 2024
arXiv /
Deep learning based uncertainty decomposition for real-time control
Neha Das, Jonas Umlauft, Armin Lederer, Alexandre Capone, Thomas Beckers, Sandra Hirche
IFAC World Congress 2023
arXiv / pdf
Robust H∞ consensus for homogeneous multi-agent systems with parametric uncertainties
Alexandre Capone, Junjie Jiao, Mostafa Zarei, Shiqi Zhang, Sandra Hirche
American Control Conference 2023
pdf /
Structure-preserving learning using Gaussian processes and variational integrators
Jan Brüdigam, Martin Schuck, Alexandre Capone, Sandra Hirche
L4DC 2022
arXiv / pdf /
Gaussian process-based stochastic model predictive control for overtaking in autonomous racing
Tim Brüdigam, Alexandre Capone, Sandra Hirche, Dirk Wollherr, Marion Leibold
ICRA 2021 Workshop - Opportunities and Challenges with Autonomous Racing
arXiv
The impact of data on the stability of learning-based control
Armin Lederer, Alexandre Capone, Thomas Beckers, Jonas Umlauft, Sandra Hirche
L4DC 2021
arXiv / pdf
Day-ahead Scheduling of Thermal Storage Systems Using Bayesian Neural Networks
Alexandre Capone, Conrad Helminger, Sandra Hirche
IEEE Transactions on Automatic Control 2024
pdf
Confidence Regions for Predictions of Online Learning-Based Control
Alexandre Capone, Armin Lederer, Sandra Hirche
IFAC World Congress 2020
pdf
Localized Active Learning of Gaussian Process State Space Models
Alexandre Capone, Jonas Umlauft, Thomas Beckers, Armin Lederer, Sandra Hirche
L4DC 2020
arXiv / pdf /
Anticipating the long-term effect of online learning in control
Alexandre Capone, Sandra Hirche
American Control Conference 2020
arXiv / pdf /
Localized Active Learning of Gaussian Process State Space Models
Alexandre Capone, Jonas Umlauft, Thomas Beckers, Armin Lederer, Sandra Hirche
L4DC 2020
arXiv / pdf /
Parameter optimization for learning-based control of control-affine systems
Armin Lederer, Alexandre Capone, Sandra Hirche
L4DC 2020
pdf
Smart forgetting for safe online learning with Gaussian processes
Jonas Umlauft, Thomas Beckers, Alexandre Capone, Armin Lederer, Sandra Hirche
L4DC 2020
arXiv / pdf /
Smart forgetting for safe online learning with Gaussian processes
Jonas Umlauft, Thomas Beckers, Alexandre Capone, Armin Lederer, Sandra Hirche
L4DC 2020
pdf
Interval observers for a class of nonlinear systems using Gaussian process models
Alexandre Capone, Sandra Hirche
European Control Conference 2019
pdf
An OPC UA-based Energy Management Platform for Multi-Energy Prosumers in District
Denis Bytschkow, Alexandre Capone, Jan Mayer, Michael Kramer, Thomas Licklederer
ENERGYCON 2019
pdf

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