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Representation Learning in Deep RL via Discrete Information Bottleneck.

, , , , , , , , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 8699-8722. PMLR, (2023)

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Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models., , , , , , , , , and . CoRR, (2022)Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information., , , , , , , , , and 1 other author(s). CoRR, (2022)Representation Learning in Deep RL via Discrete Information Bottleneck., , , , , , , , , and 1 other author(s). AISTATS, volume 206 of Proceedings of Machine Learning Research, page 8699-8722. PMLR, (2023)Cycle Consistency Driven Object Discovery., , and . CoRR, (2023)CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback., , , and . CoRR, (2022)Augmenting NLP models using Latent Feature Interpolations., , , , , and . COLING, page 6931-6936. International Committee on Computational Linguistics, (2020)Representation Learning in Deep RL via Discrete Information Bottleneck., , , , , , , , , and 1 other author(s). CoRR, (2022)Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning., , , , , , and . NeurIPS, (2022)Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning., , , , , , , , , and . NeurIPS Datasets and Benchmarks, (2021)SpeechMix - Augmenting Deep Sound Recognition Using Hidden Space Interpolations., , , , , , and . INTERSPEECH, page 861-865. ISCA, (2020)