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If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks., , , , , , , , and . Pattern Recognit. Lett., (2020)Learning Abstract and Transferable Representations for Planning., , and . CoRR, (2022)Learning Options from Demonstration using Skill Segmentation., , , and . CoRR, (2020)Learning to Follow Language Instructions with Compositional Policies., , , , , and . CoRR, (2021)Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces., , and . CoRR, (2019)Automatic encoding and repair of reactive high-level tasks with learned abstract representations., , , and . Int. J. Robotics Res., 42 (4-5): 263-288 (April 2023)World Value Functions: Knowledge Representation for Multitask Reinforcement Learning., , and . CoRR, (2022)Will it Blend? Composing Value Functions in Reinforcement Learning., , , and . CoRR, (2018)A Boolean Task Algebra for Reinforcement Learning., , and . NeurIPS, (2020)Learning Portable Representations for High-Level Planning., , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 4682-4691. PMLR, (2020)