Projects

Mastering Atari with Discrete World Models

D Hafner, T Lillicrap, M Norouzi, J Ba Preprint

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Action and Perception as Divergence Minimization

D Hafner, P Ortega, J Ba, T Parr, K Friston, N Heess Preprint

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Planning to Explore via Self-Supervised World Models

R Sekar, O Rybkin, K Daniilidis, P Abbeel, D Hafner, D Pathak ICML 2020 (22%)

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Dream to Control: Learning Behaviors by Latent Imagination

D Hafner, T Lillicrap, J Ba, M Norouzi ICLR 2020 (oral, 4%), DRLW 2019 (oral)

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A Deep Learning Framework for Neuroscience

Richards, Lillicrap, Beaudoi, Bengio, Bogacz, Christensen, Clopath, Costa, Berker, Ganguli, Gillon, Hafner, Kepecs, Kriegeskorte, Latham, Lindsay, Miller, Naud, Pack, Poirazi, Roelfsema, Sacramento, Saxe, Scellier, Schapiro, Senn, Wayne, Yamins, Zenke, Zylberberg, Therien, Kording Nature Neuroscience

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Noise Contrastive Priors for Functional Uncertainty

D Hafner, D Tran, A Irpan, T Lillicrap, J Davidson UAI 2019 (26%)

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Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion

J Buckman, D Hafner, G Tucker, E Brevdo, H Lee NeurIPS 2018 (oral, 0.6%)

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Learning Latent Dynamics for Planning from Pixels

D Hafner, T Lillicrap, I Fischer, R Villegas, D Ha, H Lee, J Davidson ICML 2019 (oral, 23%)

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Sim-to-Real: Learning Agile Locomotion For Quadruped Robots

J Tan, T Zhang, E Coumans, A Iscen, Y Bai, D Hafner, S Bohez, V Vanhoucke RSS 2018 (oral, 31%)

Paper

TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

D Hafner, J Davidson, V Vanhoucke Tech report

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Learning Hierarchical Information Flow with Recurrent Neural Modules

D Hafner, A Irpan, J Davidson, N Heess NIPS 2017 (21%)

Paper Poster

Deep Reinforcement Learning from Raw Pixels in Doom

D Hafner BSc thesis

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