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Hany Abdulsamad
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2020 – today
- 2024
- [j4]Hany Abdulsamad
, Peter Nickl
Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics. IEEE Trans. Pattern Anal. Mach. Intell. 46(4): 1950-1963 (2024) - [c15]Sahel Iqbal, Adrien Corenflos, Simo Särkkä, Hany Abdulsamad:
Nesting Particle Filters for Experimental Design in Dynamical Systems. ICML 2024 - [c14]Sahel Iqbal, Hany Abdulsamad, Tripp Cator, Ulisses Braga-Neto, Simo Särkkä:
Parallel-in-Time Probabilistic Solutions for Time-Dependent Nonlinear Partial Differential Equations. MLSP 2024: 1-6 - [i20]Sahel Iqbal, Adrien Corenflos, Simo Särkkä, Hany Abdulsamad:
Nesting Particle Filters for Experimental Design in Dynamical Systems. CoRR abs/2402.07868 (2024) - [i19]Sahel Iqbal, Hany Abdulsamad, Sara Pérez-Vieites, Simo Särkkä, Adrien Corenflos:
Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design. CoRR abs/2409.05354 (2024) - [i18]Casian Iacob, Hany Abdulsamad, Simo Särkkä:
A Parallel-in-Time Newton's Method for Nonlinear Model Predictive Control. CoRR abs/2409.20027 (2024) - 2023
- [c13]Fatemeh Yaghoobi, Hany Abdulsamad, Simo Särkkä:
A Recursive Newton Method for Smoothing in Nonlinear State Space Models. EUSIPCO 2023: 1758-1762 - [c12]Adrien Corenflos, Hany Abdulsamad:
Variational Gaussian Filtering via Wasserstein Gradient Flows. EUSIPCO 2023: 1838-1842 - [i17]Adrien Corenflos, Hany Abdulsamad:
Variational Gaussian filtering via Wasserstein gradient flows. CoRR abs/2303.06398 (2023) - [i16]Fatemeh Yaghoobi, Hany Abdulsamad, Simo Särkkä:
A Recursive Newton Method for Smoothing in Nonlinear State Space Models. CoRR abs/2306.09148 (2023) - [i15]Hany Abdulsamad, Sahel Iqbal, Adrien Corenflos, Simo Särkkä:
Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing. CoRR abs/2312.14000 (2023) - 2022
- [b1]Hany Abdulsamad:
Statistical Machine Learning for Modeling and Control of Stochastic Structured Systems. Technical University of Darmstadt, Germany, 2022 - [j3]Janosch Moos
Robust Reinforcement Learning: A Review of Foundations and Recent Advances. Mach. Learn. Knowl. Extr. 4(1): 276-315 (2022) - [i14]Tim Schneider, Boris Belousov, Hany Abdulsamad, Jan Peters:
Active Inference for Robotic Manipulation. CoRR abs/2206.10313 (2022) - [i13]Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters:
Variational Hierarchical Mixtures for Learning Probabilistic Inverse Dynamics. CoRR abs/2211.01120 (2022) - 2021
- [j2]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) - [c11]Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters:
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning. ICRA 2021: 4216-4222 - [i12]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) - [i11]Hany Abdulsamad, Tim Dorau, Boris Belousov, Jia-Jie Zhu, Jan Peters:
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions. CoRR abs/2103.15388 (2021) - [i10]Joe Watson, Hany Abdulsamad, Rolf Findeisen, Jan Peters:
Stochastic Control through Approximate Bayesian Input Inference. CoRR abs/2105.07693 (2021) - [i9]Hany Abdulsamad, Jan Peters:
Model-Based Reinforcement Learning for Stochastic Hybrid Systems. CoRR abs/2111.06211 (2021) - 2020
- [c10]Samuele Tosatto, João Carvalho, Hany Abdulsamad, Jan Peters:
A Nonparametric Off-Policy Policy Gradient. AISTATS 2020: 167-177 - [c9]Hany Abdulsamad, Jan Peters:
Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation. L4DC 2020: 904-914 - [i8]Samuele Tosatto, João Carvalho, Hany Abdulsamad, Jan Peters:
A Nonparametric Offpolicy Policy Gradient. CoRR abs/2001.02435 (2020) - [i7]Hany Abdulsamad, Jan Peters:
Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation. CoRR abs/2005.01432 (2020) - [i6]Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters:
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning. CoRR abs/2011.05217 (2020)
2010 – 2019
- 2019
- [c8]Pascal Klink, Hany Abdulsamad, Boris Belousov, Jan Peters:
Self-Paced Contextual Reinforcement Learning. CoRL 2019: 513-529 - [c7]Joe Watson, Hany Abdulsamad, Jan Peters:
Stochastic Optimal Control as Approximate Input Inference. CoRL 2019: 697-716 - [c6]Matthias Schultheis, Boris Belousov, Hany Abdulsamad, Jan Peters:
Receding Horizon Curiosity. CoRL 2019: 1278-1288 - [c5]Onur Celik, Hany Abdulsamad, Jan Peters:
Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics. IROS 2019: 6828-6833 - [i5]Onur Celik, Hany Abdulsamad, Jan Peters:
Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics. CoRR abs/1906.11003 (2019) - [i4]Pascal Klink, Hany Abdulsamad, Boris Belousov, Jan Peters:
Self-Paced Contextual Reinforcement Learning. CoRR abs/1910.02826 (2019) - [i3]Joe Watson, Hany Abdulsamad, Jan Peters:
Stochastic Optimal Control as Approximate Input Inference. CoRR abs/1910.03003 (2019) - [i2]Matthias Schultheis, Boris Belousov, Hany Abdulsamad, Jan Peters:
Receding Horizon Curiosity. CoRR abs/1910.03620 (2019) - 2018
- [j1]Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Jan Peters, Gerhard Neumann:
Model-Free Trajectory-based Policy Optimization with Monotonic Improvement. J. Mach. Learn. Res. 19: 14:1-14:25 (2018) - 2017
- [c4]Hany Abdulsamad, Oleg Arenz
State-Regularized Policy Search for Linearized Dynamical Systems. ICAPS 2017: 419-424 - 2016
- [c3]Riad Akrour, Gerhard Neumann, Hany Abdulsamad, Abbas Abdolmaleki:
Model-Free Trajectory Optimization for Reinforcement Learning. ICML 2016: 2961-2970 - [c2]Oleg Arenz
Optimal control and inverse optimal control by distribution matching. IROS 2016: 4046-4053 - [i1]Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Gerhard Neumann:
Model-free Trajectory Optimization for Reinforcement Learning. CoRR abs/1606.09197 (2016) - 2015
- [c1]Simone Parisi, Hany Abdulsamad, Alexandros Paraschos, Christian Daniel, Jan Peters:
Reinforcement learning vs human programming in tetherball robot games. IROS 2015: 6428-6434
Coauthor Index
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last updated on 2024-11-30 00:19 CET by the dblp team
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