Latent space policy search for robotics. - Kevin Sebastian Luck; Gerhard Neumann; Erik Berger; Jan Peters 001; Heni Ben Amor (IROS, 2014)

Sparse Latent Space Policy Search. - Kevin Sebastian Luck; Joni Pajarinen; Erik Berger; Ville Kyrki; Heni Ben Amor (AAAI, 2016)

Extracting bimanual synergies with reinforcement learning. - Kevin Sebastian Luck; Heni Ben Amor (IROS, 2017)

Bio-inspired Robot Design Considering Load-Bearing and Kinematic Ontogeny of Chelonioidea Sea Turtles. - Michael Andrew Jansen; Kevin Sebastian Luck; Joseph Campbell; Heni Ben Amor; Daniel M. Aukes (Living Machines, 2017)

From the Lab to the Desert: Fast Prototyping and Learning of Robot Locomotion. - Kevin Sebastian Luck; Joseph Campbell; Michael Andrew Jansen; Daniel Aukes; Heni Ben Amor (Robotics: Science and Systems, 2017)

Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning. - Kevin Sebastian Luck; Heni Ben Amor; Roberto Calandra (CoRL, 2019)

Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. - Kevin Sebastian Luck; Mel Vecerík; Simon Stepputtis; Heni Ben Amor; Jonathan Scholz (IROS, 2019)

Residual Learning from Demonstration. - Todor Davchev; Kevin Sebastian Luck; Michael Burke; Franziska Meier; Stefan Schaal; Subramanian Ramamoorthy (CoRR, 2020)

What Robot do I Need? Fast Co-Adaptation of Morphology and Control using Graph Neural Networks. - Kevin Sebastian Luck; Roberto Calandra; Michael N. Mistry (CoRR, 2021)

Residual Learning From Demonstration: Adapting DMPs for Contact-Rich Manipulation. - Todor Davchev; Kevin Sebastian Luck; Michael Burke; Franziska Meier; Stefan Schaal; Subramanian Ramamoorthy (IEEE Robotics Autom. Lett., 2022)

Co-imitation: Learning Design and Behaviour by Imitation. - Chang Rajani; Karol Arndt; David Blanco Mulero; Kevin Sebastian Luck; Ville Kyrki (AAAI, 2023)

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning. - Mhairi Dunion; Trevor McInroe; Kevin Sebastian Luck; Josiah P. Hanna; Stefano V. Albrecht (ICLR, 2023)

Co-imagination of Behaviour and Morphology of Agents. - Maria Sliacka; Michael N. Mistry; Roberto Calandra; Ville Kyrki; Kevin Sebastian Luck (LOD (1), 2023)

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. - Mhairi Dunion; Trevor McInroe; Kevin Sebastian Luck; Josiah Hanna; Stefano V. Albrecht (NeurIPS, 2023)

Practical Equivariances via Relational Conditional Neural Processes. - Daolang Huang; Manuel Haussmann; Ulpu Remes; St John; Grégoire Clarté; Kevin Sebastian Luck; Samuel Kaski; Luigi Acerbi (NeurIPS, 2023)

Practical Equivariances via Relational Conditional Neural Processes. - Daolang Huang; Manuel Haussmann; Ulpu Remes; S. T. John; Grégoire Clarté; Kevin Sebastian Luck; Samuel Kaski; Luigi Acerbi (CoRR, 2023)

Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping. - Gabriella Pizzuto; Hetong Wang; Hatem Fakhruldeen; Bei Peng 001; Kevin S. Luck; Andrew I. Cooper (CASE, 2024)

Learning Transparent Reward Models via Unsupervised Feature Selection. - Daulet Baimukashev; Gokhan Alcan; Kevin Sebastian Luck; Ville Kyrki (CoRL, 2024)

Discrete Codebook World Models for Continuous Control. - Aidan Scannell; Mohammadreza Nakhaeinezhadfard; Kalle Kujanpää; Yi Zhao 014; Kevin Sebastian Luck; Arno Solin; Joni Pajarinen (ICLR, 2025)

Virtual Laboratories: Domain-agnostic workflows for research. - Carlos Sevilla-Salcedo; Armi Tiihonen; Mahsa Asadi; Kevin Sebastian Luck; Aras Umut Erarslan; Arto Klami; Samuel Kaski (CoRR, 2025)

MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects. - Yuying Zhang; Kevin Sebastian Luck; Francesco Verdoja; Ville Kyrki; Joni Pajarinen (CoRR, 2025)