Projects Dec 10, 2018 (NeurIPS 2019, 21%) Bayesian Layers: A Module for Neural Network Uncertainty D Tran, M Dusenberry, M v d Wilk, D Hafner Nov 30, 2018 (NeurIPS 2018 DRL Workshop) Modulated Policy Hierarchies A Pashevich, D Hafner, J Davidson, R Sukthankar, C Schmid Jul 24, 2018 (UAI 2019, 26%) Noise Contrastive Priors for Functional Uncertainty D Hafner, D Tran, A Irpan, T Lillicrap, J Davidson Jul 14, 2018 (NeurIPS 2018, oral 0.6%) Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion J Buckman, D Hafner, G Tucker, E Brevdo, H Lee Jul 4, 2018 (ICML 2019, oral 23%) Learning Latent Dynamics for Planning from Pixels D Hafner, T Lillicrap, I Fischer, R Villegas, D Ha, H Lee, J Davidson Apr 27, 2018 (RSS 2018, oral 31%) 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 Nov 8, 2017 (Tech report) TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow D Hafner, J Davidson, V Vanhoucke Jul 18, 2017 (NIPS 2017, 21%) Learning Hierarchical Information Flow with Recurrent Neural Modules D Hafner, A Irpan, J Davidson, N Heess Aug 22, 2016 (ESA 2016, 27%) Probabilistic Routing for On-Street Parking Search T Arndt, D Hafner, T Kellermeier, S Krogmann, A Razmjou, M Krejca, R Rothenberger, T Friedrich Jul 15, 2016 (BSc thesis) Deep Reinforcement Learning From Raw Pixels in Doom D Hafner
