Learning inverse dynamics models in O(n) time with LSTM networks. - Elmar Rueckert; Moritz Nakatenus; Samuele Tosatto; Jan Peters 001 (Humanoids, 2017)

Boosted Fitted Q-Iteration. - Samuele Tosatto; Matteo Pirotta; Carlo D'Eramo; Marcello Restelli (ICML, 2017)

Exploration Driven by an Optimistic Bellman Equation. - Samuele Tosatto; Carlo D'Eramo; Joni Pajarinen; Marcello Restelli; Jan Peters 001 (IJCNN, 2019)

A Nonparametric Off-Policy Policy Gradient. - Samuele Tosatto; João Carvalho; Hany Abdulsamad; Jan Peters 001 (AISTATS, 2020)

A Nonparametric Offpolicy Policy Gradient. - Samuele Tosatto; João Carvalho; Hany Abdulsamad; Jan Peters 001 (CoRR, 2020)

An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions. - Samuele Tosatto; Riad Akrour; Jan Peters 001 (CoRR, 2020)

Dimensionality Reduction of Movement Primitives in Parameter Space. - Samuele Tosatto; Jonas Stadtmueller; Jan Peters 001 (CoRR, 2020)

Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills. - Samuele Tosatto; Georgia Chalvatzaki; Jan Peters 001 (ICRA, 2021)

Off-Policy Reinforcement Learning for Robotics. - Samuele Tosatto (2021)

An Alternate Policy Gradient Estimator for Softmax Policies. - Shivam Garg 006; Samuele Tosatto; Yangchen Pan; Martha White; Rupam Mahmood (AISTATS, 2022)

Model-free Policy Learning with Reward Gradients. - Qingfeng Lan; Samuele Tosatto; Homayoon Farrahi; Rupam Mahmood (AISTATS, 2022)

A Temporal-Difference Approach to Policy Gradient Estimation. - Samuele Tosatto; Andrew Patterson; Martha White; Rupam Mahmood (ICML, 2022)

Variable-Decision Frequency Option Critic. - Amirmohammad Karimi; Jun Jin 001; Jun Luo 009; A. Rupam Mahmood; Martin Jägersand; Samuele Tosatto (CoRR, 2022)

Batch Reinforcement Learning With a Nonparametric Off-Policy Policy Gradient. - Samuele Tosatto; João Carvalho; Jan Peters 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Dynamic Decision Frequency with Continuous Options. - Amirmohammad Karimi; Jun Jin 001; Jun Luo 009; A. Rupam Mahmood; Martin Jägersand; Samuele Tosatto (IROS, 2023)

Deep Probabilistic Movement Primitives with a Bayesian Aggregator. - Michael Przystupa; Faezeh Haghverd; Martin Jägersand; Samuele Tosatto (IROS, 2023)

Local Linearity is All You Need (in Data-Driven Teleoperation). - Michael Przystupa; Gauthier Gidel; Matthew E. Taylor; Martin Jägersand; Justus H. Piater; Samuele Tosatto (IROS, 2024)

Investigating the Benefits of Nonlinear Action Maps in Data-Driven Teleoperation. - Michael Przystupa; Gauthier Gidel; Matthew E. Taylor; Martin Jägersand; Justus H. Piater; Samuele Tosatto (CoRR, 2024)