Matteo Hessel
Matteo Hessel
Research Engineer, Google DeepMind
Verified email at google.com
TitleCited byYear
Dueling Network Architectures for Deep Reinforcement Learning
Z Wang, T Schaul, M Hessel, H Van Hasselt, M Lanctot, N De Freitas
International Conference on Machine Learning (ICML 2016), 1995–2003, 2016
5262016
Rainbow: Combining Improvements in Deep Reinforcement Learning
M Hessel, J Modayil, H van Hasselt, T Schaul, G Ostrovski, W Dabney, ...
Association for the Advancement of Artificial Intelligence (AAAI 2018), 2017
1712017
The predictron: End-to-end learning and planning
D Silver, H van Hasselt, M Hessel, T Schaul, A Guez, T Harley, ...
International Conference on Machine Learning (ICML 2017), 3191--3199, 2016
732016
Distributed Prioritized Experience Replay
D Horgan, J Quan, D Budden, G Barth-Maron, M Hessel, H van Hasselt, ...
International Conference on Learning Representations (ICLR 2018), 2018
512018
Learning values across many orders of magnitude
HP van Hasselt, A Guez, M Hessel, V Mnih, D Silver
Advances In Neural Information Processing Systems (NIPS 2016), 4287-4295, 2016
382016
Observe and Look Further: Achieving Consistent Performance on Atari
T Pohlen, B Piot, T Hester, MG Azar, D Horgan, D Budden, G Barth-Maron, ...
arXiv preprint arXiv:1805.11593, 2018
202018
Multi-task Deep Reinforcement Learning with PopArt
M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H van Hasselt
Association for the Advancement of Artificial Intelligence (AAAI 2019), 2018
122018
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
A Barreto, D Borsa, J Quan, T Schaul, D Silver, M Hessel, D Mankowitz, ...
International Conference on Machine Learning (ICML 2018), 510-519, 2018
102018
Unicorn: Continual Learning with a Universal, Off-policy Agent
DJ Mankowitz, A Žídek, A Barreto, D Horgan, M Hessel, J Quan, J Oh, ...
arXiv preprint arXiv:1802.08294, 2018
72018
Deep Reinforcement Learning and the Deadly Triad
H van Hasselt, Y Doron, F Strub, M Hessel, N Sonnerat, J Modayil
Deep Reinforcement Learning Workshop (NeurIPS 2018), 2018
32018
Automatic Tuning of Computational Models
M Hessel, F Ortalli, F Borgatelli, PL Lanzi
Simulation and Modeling Methodologies, Technologies and Applications, 43-64, 2015
2*2015
Scaling shared model governance via model splitting
M Martic, J Leike, A Trask, M Hessel, S Legg, P Kohli
arXiv preprint arXiv:1812.05979, 2018
2018
On Inductive Biases in Deep Reinforcement Learning
M Hessel, H van Hasselt, J Modayil, D Silver
2018
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Articles 1–13