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Latest external collaboration on country level. Dive into details by clicking on the dots.

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Dive into the research topics where Matteo Hessel is active.

Publication


Featured researches published by Matteo Hessel.


international conference on machine learning | 2016

Dueling network architectures for deep reinforcement learning

Ziyu Wang; Tom Schaul; Matteo Hessel; Hado van Hasselt; Marc Lanctot; Nando de Freitas


international conference on machine learning | 2017

The Predictron: End-To-End Learning and Planning

David Silver; Hado van Hasselt; Matteo Hessel; Tom Schaul; Arthur Guez; Tim Harley; Gabriel Dulac-Arnold; David P. Reichert; Neil C. Rabinowitz; André da Motta Salles Barreto; Thomas Degris


national conference on artificial intelligence | 2018

Rainbow: Combining Improvements in Deep Reinforcement Learning

Matteo Hessel; Joseph Modayil; Hado van Hasselt; Tom Schaul; Georg Ostrovski; Will Dabney; Dan Horgan; David Silver


international conference on learning representations | 2018

Noisy Networks For Exploration

Meire Fortunato; Mohammad Gheshlaghi Azar; Jacob Menick; Matteo Hessel; Ian Osband; Alex Graves; Volodymyr Mnih; Rémi Munos; Demis Hassabis; Olivier Pietquin; Charles Blundell; Shane Legg


neural information processing systems | 2016

Learning values across many orders of magnitude

Hado van Hasselt; Arthur Guez; Matteo Hessel; Volodymyr Mnih; David Silver


international conference on learning representations | 2018

Distributed Prioritized Experience Replay

Dan Horgan; John Quan; David Budden; Gabriel Barth-Maron; Matteo Hessel; Hado van Hasselt; David Silver


arXiv: Learning | 2018

Unicorn: Continual Learning with a Universal, Off-policy Agent.

Daniel J. Mankowitz; Augustin Zidek; André da Motta Salles Barreto; Dan Horgan; Matteo Hessel; John Quan; Junhyuk Oh; Hado van Hasselt; David Silver; Tom Schaul


arXiv: Learning | 2018

Observe and Look Further: Achieving Consistent Performance on Atari.

Tobias Pohlen; Todd Hester; Mohammad Gheshlaghi Azar; Dan Horgan; David Budden; Gabriel Barth-Maron; Hado van Hasselt; John Quan; Mel Večerík; Matteo Hessel; Rémi Munos; Olivier Pietquin


international conference on machine learning | 2018

Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement

André da Motta Salles Barreto; Diana Borsa; John Quan; Tom Schaul; David Silver; Matteo Hessel; Daniel J. Mankowitz; Augustin Zidek; Rémi Munos


arXiv: Learning | 2018

Multi-task Deep Reinforcement Learning with PopArt

Matteo Hessel; Hubert Soyer; Lasse Espeholt; Wojciech Marian Czarnecki; Simon Schmitt; Hado van Hasselt

Collaboration


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André da Motta Salles Barreto

University of Massachusetts Amherst

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Daniel J. Mankowitz

Technion – Israel Institute of Technology

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