Reinforcement learning vs human programming in tetherball robot games. - Simone Parisi; Hany Abdulsamad; Alexandros Paraschos; Christian Daniel; Jan Peters 001 (IROS, 2015)

Model-Free Trajectory Optimization for Reinforcement Learning. - Riad Akrour; Gerhard Neumann; Hany Abdulsamad; Abbas Abdolmaleki (ICML, 2016)

Optimal control and inverse optimal control by distribution matching. - Oleg Arenz; Hany Abdulsamad; Gerhard Neumann (IROS, 2016)

State-Regularized Policy Search for Linearized Dynamical Systems. - Hany Abdulsamad; Oleg Arenz; Jan Peters 001; Gerhard Neumann (ICAPS, 2017)

Model-Free Trajectory-based Policy Optimization with Monotonic Improvement. - Riad Akrour; Abbas Abdolmaleki; Hany Abdulsamad; Jan Peters 001; Gerhard Neumann (J. Mach. Learn. Res., 2018)

Self-Paced Contextual Reinforcement Learning. - Pascal Klink; Hany Abdulsamad; Boris Belousov; Jan Peters 001 (CoRL, 2019)

Receding Horizon Curiosity. - Matthias Schultheis; Boris Belousov; Hany Abdulsamad; Jan Peters 001 (CoRL, 2019)

Stochastic Optimal Control as Approximate Input Inference. - Joe Watson; Hany Abdulsamad; Jan Peters 001 (CoRL, 2019)

Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics. - Onur Celik; Hany Abdulsamad; Jan Peters 001 (IROS, 2019)

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

Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation. - Hany Abdulsamad; Jan Peters 001 (L4DC, 2020)

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

A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning. - Hany Abdulsamad; Peter Nickl; Pascal Klink; Jan Peters 001 (ICRA, 2021)

Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions. - Hany Abdulsamad; Tim Dorau; Boris Belousov; Jia-Jie Zhu; Jan Peters 001 (CoRR, 2021)

Stochastic Control through Approximate Bayesian Input Inference. - Joe Watson; Hany Abdulsamad; Rolf Findeisen; Jan Peters 001 (CoRR, 2021)

Model-Based Reinforcement Learning for Stochastic Hybrid Systems. - Hany Abdulsamad; Jan Peters 001 (CoRR, 2021)

A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. - Pascal Klink; Hany Abdulsamad; Boris Belousov; Carlo D'Eramo; Jan Peters 001; Joni Pajarinen (J. Mach. Learn. Res., 2021)

Active Inference for Robotic Manipulation. - Tim Schneider; Boris Belousov; Hany Abdulsamad; Jan Peters 001 (CoRR, 2022)

Variational Hierarchical Mixtures for Learning Probabilistic Inverse Dynamics. - Hany Abdulsamad; Peter Nickl; Pascal Klink; Jan Peters 001 (CoRR, 2022)

Robust Reinforcement Learning: A Review of Foundations and Recent Advances. - Janosch Moos; Kay Hansel; Hany Abdulsamad; Svenja Stark; Debora Clever; Jan Peters 001 (Mach. Learn. Knowl. Extr., 2022)

Statistical Machine Learning for Modeling and Control of Stochastic Structured Systems. - Hany Abdulsamad (2022)

Variational Gaussian Filtering via Wasserstein Gradient Flows. - Adrien Corenflos; Hany Abdulsamad (EUSIPCO, 2023)

A Recursive Newton Method for Smoothing in Nonlinear State Space Models. - Fatemeh Yaghoobi; Hany Abdulsamad; Simo Särkkä (EUSIPCO, 2023)

Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing. - Hany Abdulsamad; Sahel Iqbal; Adrien Corenflos; Simo Särkkä (CoRR, 2023)

Nesting Particle Filters for Experimental Design in Dynamical Systems. - Sahel Iqbal; Adrien Corenflos; Simo Särkkä; Hany Abdulsamad (ICML, 2024)

Parallel-in-Time Probabilistic Solutions for Time-Dependent Nonlinear Partial Differential Equations. - Sahel Iqbal; Hany Abdulsamad; Tripp Cator; Ulisses Braga-Neto; Simo Särkkä (MLSP, 2024)

Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design. - Sahel Iqbal; Hany Abdulsamad; Sara Pérez-Vieites; Simo Särkkä; Adrien Corenflos (CoRR, 2024)

A Parallel-in-Time Newton's Method for Nonlinear Model Predictive Control. - Casian Iacob; Hany Abdulsamad; Simo Särkkä (CoRR, 2024)

Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics. - Hany Abdulsamad; Peter Nickl; Pascal Klink; Jan Peters 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Sequential Monte Carlo for Policy Optimization in Continuous POMDPs. - Hany Abdulsamad; Sahel Iqbal; Simo Särkkä (CoRR, 2025)