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ORCIDMatteo Turchetta
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2020 – today
- 2024
[i16]Manish Prajapat, Johannes Köhler
, Matteo Turchetta, Andreas Krause, Melanie N. Zeilinger:
Safe Guaranteed Exploration for Non-linear Systems. CoRR abs/2402.06562 (2024)- [i15]Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Matteo Turchetta:
Breeding Programs Optimization with Reinforcement Learning. CoRR abs/2406.03932 (2024) - 2023
- [j3]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: 103922 (2023) - [j2]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) - 2022
- [c12]Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause:
Near-Optimal Multi-Agent Learning for Safe Coverage Control. NeurIPS 2022 - [c11]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 - [i14]Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann:
Scalable Safe Exploration for Global Optimization of Dynamical Systems. CoRR abs/2201.09562 (2022) - [i13]Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause:
Near-Optimal Multi-Agent Learning for Safe Coverage Control. CoRR abs/2210.06380 (2022) - 2021
- [b1]Matteo Turchetta:
Safety and Robustness in Reinforcement Learning. ETH Zurich, Zürich, Switzerland, 2021 - [c10]Dominik Baumann, Alonso Marco, Matteo Turchetta, Sebastian Trimpe:
GoSafe: Globally Optimal Safe Robot Learning. ICRA 2021: 4452-4458 - [c9]Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause:
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA 2021: 9782-9788 - [c8]David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause:
Information Directed Reward Learning for Reinforcement Learning. NeurIPS 2021: 3850-3862 - [i12]Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause:
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. CoRR abs/2101.07825 (2021) - [i11]David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause:
Information Directed Reward Learning for Reinforcement Learning. CoRR abs/2102.12466 (2021) - [i10]Dominik Baumann, Alonso Marco, Matteo Turchetta, Sebastian Trimpe:
GoSafe: Globally Optimal Safe Robot Learning. CoRR abs/2105.13281 (2021) - 2020
- [c7]Matteo Turchetta, Andreas Krause, Sebastian Trimpe:
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA 2020: 10702-10708 - [c6]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. IJCAI 2020: 2633-2639 - [c5]Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal:
Safe Reinforcement Learning via Curriculum Induction. NeurIPS 2020 - [i9]Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal:
Safe Reinforcement Learning via Curriculum Induction. CoRR abs/2006.12136 (2020)
2010 – 2019
- 2019
- [c4]Matteo Turchetta, Felix Berkenkamp, Andreas Krause:
Safe Exploration for Interactive Machine Learning. NeurIPS 2019: 2887-2897 - [i8]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Joschka Boedecker, Andreas Krause:
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR abs/1906.12189 (2019) - [i7]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. CoRR abs/1907.01329 (2019) - [i6]Matteo Turchetta, Andreas Krause, Sebastian Trimpe:
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. CoRR abs/1910.13399 (2019) - [i5]Matteo Turchetta, Felix Berkenkamp, Andreas Krause:
Safe Exploration for Interactive Machine Learning. CoRR abs/1910.13726 (2019) - 2018
- [j1]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): 4423-4430 (2018) - [c3]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause:
Learning-Based Model Predictive Control for Safe Exploration. CDC 2018: 6059-6066 - [i4]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause:
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR abs/1803.08287 (2018) - [i3]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 abs/1805.07095 (2018) - 2017
- [c2]Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause:
Safe Model-based Reinforcement Learning with Stability Guarantees. NIPS 2017: 908-918 - [i2]Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause:
Safe Model-based Reinforcement Learning with Stability Guarantees. CoRR abs/1705.08551 (2017) - 2016
- [c1]Matteo Turchetta, Felix Berkenkamp, Andreas Krause:
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. NIPS 2016: 4305-4313 - [i1]Matteo Turchetta, Felix Berkenkamp, Andreas Krause:
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. CoRR abs/1606.04753 (2016)
Coauthor Index
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last updated on 2024-10-07 22:07 CEST by the dblp team
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