Matteo Hessel
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
16
Venues
4
Active years
2014–2022
Best venue rank
A*
Where they publish
Papers
16 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2022 | ICLR | Learning by Directional Gradient Descent. | David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt |
| 2021 | AAAI | Expected Eligibility Traces. | Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, Andr Barreto, Diana Borsa |
| 2021 | ICML | Muesli: Combining Improvements in Policy Optimization. | Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt |
| 2021 | ICML | Emphatic Algorithms for Deep Reinforcement Learning. | Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt |
| 2020 | ICLR | Behaviour Suite for Reinforcement Learning. | Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvri, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt |
| 2020 | ICML | Off-Policy Actor-Critic with Shared Experience Replay. | Simon Schmitt, Matteo Hessel, Karen Simonyan |
| 2020 | ICML | What Can Learned Intrinsic Rewards Capture? | Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh |
| 2019 | AAAI | Multi-Task Deep Reinforcement Learning with PopArt. | Matteo Hessel, Hubert Soyer, Lasse Espeholt, Wojciech Czarnecki, Simon Schmitt, Hado van Hasselt |
| 2018 | AAAI | Rainbow: Combining Improvements in Deep Reinforcement Learning. | Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver |
| 2018 | ICLR | Noisy Networks For Exploration. | Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Rmi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg |
| 2018 | ICLR | Distributed Prioritized Experience Replay. | Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver |
| 2018 | ICML | Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. | Andr Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zdek, Rmi Munos |
| 2017 | ICML | 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, Andr Barreto, Thomas Degris |
| 2016 | ICML | Dueling Network Architectures for Deep Reinforcement Learning. | Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas |
| 2014 | SIMULTECH | A novel approach to model design and tuning through automatic parameter screening and optimization theory and application to a helicopter flight simulator case-study. | Matteo Hessel, Francesco Borgatelli, Fabio Ortalli |
| 2014 | SIMULTECH | Automatic Tuning of Computational Models. | Matteo Hessel, Fabio Ortalli, Francesco Borgatelli, Pier Luca Lanzi |