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ORCIDCarlo D'Eramo
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2020 – today
- 2024
[j7]Pascal Klink
, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(11): 7191-7204 (2024)- [c23]Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo:
Parameterized Projected Bellman Operator. AAAI 2024: 15402-15410 - [c22]Ahmed Hendawy, Jan Peters, Carlo D'Eramo:
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. ICLR 2024 - [c21]Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo:
Augmented Bayesian Policy Search. ICLR 2024 - [c20]Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo:
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. ICLR 2024 - [c19]Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki:
Domain Randomization via Entropy Maximization. ICLR 2024 - [c18]Erdi Sayar, Zhenshan Bing, Carlo D'Eramo, Ozgur S. Oguz, Alois Knoll:
Contact Energy Based Hindsight Experience Prioritization. ICRA 2024: 5434-5440 - [c17]Anna Riedmann, Julia Götz, Carlo D'Eramo, Birgit Lugrin:
Uli-RL: A Real-World Deep Reinforcement Learning Pedagogical Agent for Children. KI 2024: 316-323 - [c16]Oliver Järnefelt, Mahdi Kallel, Carlo D'Eramo:
Cyclicity-Regularized Coordination Graphs. RLC 2024: 366-379 - [i22]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. CoRR abs/2401.09561 (2024) - [i21]Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo:
Iterated Q-Network: Beyond the One-Step Bellman Operator. CoRR abs/2403.02107 (2024) - [i20]Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo:
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning. CoRR abs/2405.16195 (2024) - [i19]Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo:
Augmented Bayesian Policy Search. CoRR abs/2407.04864 (2024) - [i18]Joe Watson, Chen Song, Oliver Weeger, Theo Gruner, An T. Le, Kay Hansel, Ahmed Hendawy, Oleg Arenz, Will Trojak, Miles Cranmer, Carlo D'Eramo, Fabian Bülow, Tanmay Goyal, Jan Peters, Martin W. Hoffman:
Machine Learning with Physics Knowledge for Prediction: A Survey. CoRR abs/2408.09840 (2024) - 2023
- [j6]Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters:
Composable energy policies for reactive motion generation and reinforcement learning. Int. J. Robotics Res. 42(10): 827-858 (2023) - [i17]Tuan Dam, Pascal Stenger, Lukas Schneider, Joni Pajarinen, Carlo D'Eramo, Odalric-Ambrym Maillard:
Monte-Carlo tree search with uncertainty propagation via optimal transport. CoRR abs/2309.10737 (2023) - [i16]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. CoRR abs/2309.14091 (2023) - [i15]Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo:
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. CoRR abs/2311.01642 (2023) - [i14]Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki:
Domain Randomization via Entropy Maximization. CoRR abs/2311.01885 (2023) - [i13]Ahmed Hendawy, Jan Peters, Carlo D'Eramo:
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. CoRR abs/2311.11385 (2023) - [i12]Erdi Sayar, Zhenshan Bing, Carlo D'Eramo, Ozgur S. Oguz, Alois Knoll:
Contact Energy Based Hindsight Experience Prioritization. CoRR abs/2312.02677 (2023) - [i11]Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo:
Parameterized Projected Bellman Operator. CoRR abs/2312.12869 (2023) - 2022
- [j5]Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms 15(3): 81 (2022) - [c15]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Boosted Curriculum Reinforcement Learning. ICLR 2022 - [c14]Pascal Klink, Haoyi Yang, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Curriculum Reinforcement Learning via Constrained Optimal Transport. ICML 2022: 11341-11358 - [c13]Carlo D'Eramo, Georgia Chalvatzaki:
Prioritized Sampling with Intrinsic Motivation in Multi-Task Reinforcement Learning. IJCNN 2022: 1-8 - [i10]Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search. CoRR abs/2202.07071 (2022) - 2021
- [j4]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. 22: 131:1-131:5 (2021) - [j3]Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. J. Mach. Learn. Res. 22: 182:1-182:52 (2021) - [j2]Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli:
Gaussian Approximation for Bias Reduction in Q-Learning. J. Mach. Learn. Res. 22: 277:1-277:51 (2021) - [c12]Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Convex Regularization in Monte-Carlo Tree Search. ICML 2021: 2365-2375 - [c11]Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D'Eramo, Aaron M. Dollar, Jan Peters:
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning. ICRA 2021: 6672-6678 - [c10]Julen Urain, Puze Liu, Anqi Li, Carlo D'Eramo, Jan Peters:
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning. Robotics: Science and Systems 2021 - [i9]Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. CoRR abs/2102.13176 (2021) - [i8]Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D'Eramo, Aaron M. Dollar, Jan Peters:
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning. CoRR abs/2103.13842 (2021) - [i7]Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters:
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning. CoRR abs/2105.04962 (2021) - 2020
- [j1]Dorothea Koert, Maximilian Kircher, Vildan Salikutluk, Carlo D'Eramo, Jan Peters:
Multi-Channel Interactive Reinforcement Learning for Sequential Tasks. Frontiers Robotics AI 7: 97 (2020) - [c9]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR 2020 - [c8]Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Generalized Mean Estimation in Monte-Carlo Tree Search. IJCAI 2020: 2397-2404 - [c7]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Self-Paced Deep Reinforcement Learning. NeurIPS 2020 - [i6]Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning. CoRR abs/2001.00119 (2020) - [i5]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. CoRR abs/2001.01102 (2020) - [i4]Andrea Cini, Carlo D'Eramo, Jan Peters, Cesare Alippi:
Deep Reinforcement Learning with Weighted Q-Learning. CoRR abs/2003.09280 (2020) - [i3]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Self-Paced Deep Reinforcement Learning. CoRR abs/2004.11812 (2020) - [i2]Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Convex Regularization in Monte-Carlo Tree Search. CoRR abs/2007.00391 (2020)
2010 – 2019
- 2019
- [b1]Carlo D'Eramo:
On the exploitation of uncertainty to improve Bellman updates and exploration in Reinforcement Learning. Polytechnic University of Milan, Italy, 2019 - [c6]Carlo D'Eramo, Andrea Cini, Marcello Restelli:
Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning. IJCNN 2019: 1-8 - [c5]Samuele Tosatto, Carlo D'Eramo, Joni Pajarinen, Marcello Restelli, Jan Peters:
Exploration Driven by an Optimistic Bellman Equation. IJCNN 2019: 1-8 - [i1]Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Generalized Mean Estimation in Monte-Carlo Tree Search. CoRR abs/1911.00384 (2019) - 2017
- [c4]Carlo D'Eramo, Alessandro Nuara, Matteo Pirotta, Marcello Restelli:
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems. AAAI 2017: 1840-1846 - [c3]Samuele Tosatto, Matteo Pirotta, Carlo D'Eramo, Marcello Restelli:
Boosted Fitted Q-Iteration. ICML 2017: 3434-3443 - [c2]Davide Tateo, Carlo D'Eramo, Alessandro Nuara, Marcello Restelli, Andrea Bonarini:
Exploiting structure and uncertainty of Bellman updates in Markov decision processes. SSCI 2017: 1-8 - 2016
- [c1]Carlo D'Eramo, Marcello Restelli, Alessandro Nuara:
Estimating Maximum Expected Value through Gaussian Approximation. ICML 2016: 1032-1040
Coauthor Index
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