Averaging rewards as a first approach towards Interpolated Experience Replay. - Wenzel Pilar von Pilchau (GI-Jahrestagung (Workshops), 2019)

An Architectural Design for Measurement Uncertainty Evaluation in Cyber-Physical Systems. - Wenzel Pilar von Pilchau; Varun Gowtham; Maximilian Gruber; Matthias Riedl; Nikolaos-Stefanos Koutrakis; Jawad Tayyub; Jörg Hähner; Sascha Eichstädt; Eckart Uhlmann; Julian Polte; Volker Frey; Alexander Willner (FedCSIS (Position Papers), 2020)

Bootstrapping a DQN Replay Memory with Synthetic Experiences. - Wenzel Baron Pilar von Pilchau; Anthony Stein; Jörg Hähner (IJCCI, 2020)

Synthetic Experiences for Accelerating DQN Performance in Discrete Non-Deterministic Environments. - Wenzel Pilar von Pilchau; Anthony Stein; Jörg Hähner (Algorithms, 2021)

Semi-model-Based Reinforcement Learning in Organic Computing Systems. - Wenzel Pilar von Pilchau; Anthony Stein; Jörg Hähner (ARCS, 2022)

Application of Uncertainty-Aware Sensor Fusion in Physical Sensor Networks. - Maximilian Gruber; Wenzel Pilar von Pilchau; Varun Gowtham; Nikolaos-Stefanos Koutrakis; Nicolas Schönborn; Sascha Eichstädt; Jörg Hähner; Marius Iulian Corici; Thomas Magedanz; Julian Polte; Eckart Uhlmann (I2MTC, 2022)

Interpolated Experience Replay for Continuous Environments. - Wenzel Pilar von Pilchau; Anthony Stein; Jörg Hähner (IJCCI, 2022)

Deep Q-Network Updates for the Full Action-Space Utilizing Synthetic Experiences. - Wenzel Pilar von Pilchau; David Pätzel; Anthony Stein; Jörg Hähner (IJCNN, 2023)

Interpolation assisted deep reinforcement learning / Wenzel Baron Pilar von Pilchau ; Betreuer: Jörg Hähner. - Wenzel Pilar von Pilchau (2024)