Matteo Turchetta

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 31

Top Topics

Global Optimization

Guided Exploration

Dynamical Systems

Reinforcement Learning

Top Venues

Publications

Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Matteo Turchetta
Breeding Programs Optimization with Reinforcement Learning. CoRR (2024)
Manish Prajapat, Johannes Köhler, Matteo Turchetta, Andreas Krause, Melanie N. Zeilinger
Safe Guaranteed Exploration for Non-linear Systems. CoRR (2024)
Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. Artif. Intell. 320 (2023)
Omar G. Younis, Matteo Turchetta, Daniel Ariza Suarez, Steven Yates, Bruno Studer, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Luca Corinzia
ChromaX: a fast and scalable breeding program simulator. Bioinform. 39 (12) (2023)
Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis Athanasiadis, Joachim M. Buhmann, Andreas Krause
Learning Long-Term Crop Management Strategies with CyclesGym. NeurIPS (2022)
Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
Scalable Safe Exploration for Global Optimization of Dynamical Systems. CoRR (2022)
Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause
Near-Optimal Multi-Agent Learning for Safe Coverage Control. CoRR (2022)
Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause
Near-Optimal Multi-Agent Learning for Safe Coverage Control. NeurIPS (2022)
Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA (2021)
Dominik Baumann, Alonso Marco, Matteo Turchetta, Sebastian Trimpe
GoSafe: Globally Optimal Safe Robot Learning. CoRR (2021)
Dominik Baumann, Alonso Marco, Matteo Turchetta, Sebastian Trimpe
GoSafe: Globally Optimal Safe Robot Learning. ICRA (2021)
Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. CoRR (2021)
David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
Information Directed Reward Learning for Reinforcement Learning. NeurIPS (2021)
David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
Information Directed Reward Learning for Reinforcement Learning. CoRR (2021)
Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
Mixed-Variable Bayesian Optimization. IJCAI (2020)
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
Safe Reinforcement Learning via Curriculum Induction. NeurIPS (2020)
Matteo Turchetta, Andreas Krause, Sebastian Trimpe
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA (2020)
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
Safe Reinforcement Learning via Curriculum Induction. CoRR (2020)
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
Safe Exploration for Interactive Machine Learning. NeurIPS (2019)
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
Safe Exploration for Interactive Machine Learning. CoRR (2019)
Matteo Turchetta, Andreas Krause, Sebastian Trimpe
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. CoRR (2019)
Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
Mixed-Variable Bayesian Optimization. CoRR (2019)
Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Joschka Boedecker, Andreas Krause
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR (2019)
Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, Juan I. Nieto
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations. IEEE Robotics Autom. Lett. 3 (4) (2018)
Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, Juan I. Nieto
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations. CoRR (2018)
Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause
Learning-Based Model Predictive Control for Safe Exploration. CDC (2018)
Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR (2018)
Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause
Safe Model-based Reinforcement Learning with Stability Guarantees. NIPS (2017)
Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause
Safe Model-based Reinforcement Learning with Stability Guarantees. CoRR (2017)
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. CoRR (2016)
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. NIPS (2016)