Lasse Espeholt

19 papers A* 4Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Deep Learning for Day Forecasts from Sparse Observations. CoRR Marcin Andrychowicz, Lasse Espeholt, Di Li, Samier Merchant, Alex Merose, Fred Zyda, Shreya Agrawal, Nal Kalchbrenner
2022	J	`jnl`	Boosting Search Engines with Interactive Agents. Trans. Mach. Learn. Res. Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher, Sascha Rothe, Pier Giuseppe Sessa, Lierni Sestorain
2021	J	`jnl`	Agent-Centric Representations for Multi-Agent Reinforcement Learning. CoRR Wenling Shang, Lasse Espeholt, Anton Raichuk, Tim Salimans
2021	J	`jnl`	Boosting Search Engines with Interactive Agents. CoRR Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher
2021	J	`jnl`	Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks. CoRR Lasse Espeholt, Shreya Agrawal, Casper Kaae Sønderby, Manoj Kumar, Jonathan Heek, Carla Bromberg, Cenk Gazen, Jason Hickey, Aaron Bell, Nal Kalchbrenner
2020	A*	`conf`	Google Research Football: A Novel Reinforcement Learning Environment. AAAI Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
2020	J	`jnl`	MetNet: A Neural Weather Model for Precipitation Forecasting. CoRR Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek, Mostafa Dehghani, Avital Oliver, Tim Salimans, Shreya Agrawal, Jason Hickey, Nal Kalchbrenner
2020	A*	`conf`	SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. ICLR Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski
2019	J	`jnl`	Google Research Football: A Novel Reinforcement Learning Environment. CoRR Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
2019	A*	`conf`	Multi-Task Deep Reinforcement Learning with PopArt. AAAI Matteo Hessel, Hubert Soyer, Lasse Espeholt, Wojciech Czarnecki, Simon Schmitt, Hado van Hasselt
2019	J	`jnl`	SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. CoRR Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski
2018	A*	`conf`	IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. ICML Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
2018	J	`jnl`	IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. CoRR Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
2018	J	`jnl`	Multi-task Deep Reinforcement Learning with PopArt. CoRR Matteo Hessel, Hubert Soyer, Lasse Espeholt, Wojciech Czarnecki, Simon Schmitt, Hado van Hasselt
2016	—	`conf`	Conditional Image Generation with PixelCNN Decoders. NIPS Aäron van den Oord, Nal Kalchbrenner, Lasse Espeholt, Koray Kavukcuoglu, Oriol Vinyals, Alex Graves
2016	J	`jnl`	Conditional Image Generation with PixelCNN Decoders. CoRR Aäron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu
2016	J	`jnl`	Neural Machine Translation in Linear Time. CoRR Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, Aäron van den Oord, Alex Graves, Koray Kavukcuoglu
2015	—	`conf`	Teaching Machines to Read and Comprehend. NIPS Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom
2015	J	`jnl`	Teaching Machines to Read and Comprehend. CoRR Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom