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Danijar Hafner
Danijar Hafner
Google Brain & University of Toronto
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Learning Latent Dynamics for Planning from Pixels
D Hafner, T Lillicrap, I Fischer, R Villegas, D Ha, H Lee, J Davidson
Proceedings of the International Conference on Machine Learning (ICML), 2019
7072019
Sim-to-Real: Learning Agile Locomotion for Quadruped Robots
J Tan, T Zhang, E Coumans, A Iscen, Y Bai, D Hafner, S Bohez, ...
Proceedings of Robotics: Science and Systems (RSS), 2018
4682018
Dream to Control: Learning Behaviors by Latent Imagination
D Hafner, T Lillicrap, J Ba, M Norouzi
International Conference on Learning Representations (ICLR), 2019
4242019
A Deep Learning Framework for Neuroscience
BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ...
Nature Neuroscience 22 (11), 2019
4012019
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
J Buckman, D Hafner, G Tucker, E Brevdo, H Lee
Advances in Neural Information Processing Systems (NeurIPS), 2018
2162018
Mastering Atari with Discrete World Models
D Hafner, T Lillicrap, M Norouzi, J Ba
International Conference on Learning Representations (ICLR), 2020
1342020
Planning to Explore via Self-Supervised World Models
R Sekar, O Rybkin, K Daniilidis, P Abbeel, D Hafner, D Pathak
Proceedings of the International Conference on Machine Learning (ICML), 2020
1182020
Bayesian Layers: A Module for Neural Network Uncertainty
D Tran, M Dusenberry, M van der Wilk, D Hafner
Advances in Neural Information Processing Systems (NeurIPS), 2019
792019
Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
D Hafner, D Tran, T Lillicrap, A Irpan, J Davidson
Uncertainty in Artificial Intelligence (UAI), 2018
582018
Sophisticated Inference
K Friston, L Da Costa, D Hafner, C Hesp, T Parr
Neural Computation 33 (3), 713-763, 2021
552021
Noise Contrastive Priors for Functional Uncertainty
D Hafner, D Tran, T Lillicrap, A Irpan, J Davidson
Uncertainty in Artificial Intelligence (UAI), 2019
472019
TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow
D Hafner, J Davidson, V Vanhoucke
Technical report, 2017
462017
Action and Perception as Divergence Minimization
D Hafner, PA Ortega, J Ba, T Parr, K Friston, N Heess
arXiv preprint arXiv:2009.01791, 2020
312020
TensorFlow for Machine Intelligence
S Abrahams, D Hafner, E Erwitt, A Scarpinelli
Bleeding Edge Press, 2016
282016
Modulated Policy Hierarchies
A Pashevich, D Hafner, J Davidson, R Sukthankar, C Schmid
Deep Reinforcement Learning Workshop (DRLW), 2018
112018
Learning Hierarchical Information Flow with Recurrent Neural Modules
D Hafner, A Irpan, J Davidson, N Heess
Advances in Neural Information Processing Systems (NIPS), 2017
102017
Deep Reinforcement Learning From Raw Pixels in Doom
D Hafner
Hasso Plattner Institute, Potsdam, Germany, 2016
92016
Probabilistic Routing for On-Street Parking Search
T Arndt, D Hafner, T Kellermeier, S Krogmann, A Razmjou, MS Krejca, ...
Annual European Symposium on Algorithms (ESA), 2016
92016
Benchmarking the Spectrum of Agent Capabilities
D Hafner
International Conference on Learning Representations (ICLR), 2021
82021
Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning
M Babaeizadeh, MT Saffar, D Hafner, H Kannan, C Finn, S Levine, ...
arXiv preprint arXiv:2012.04603, 2020
82020
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Articles 1–20