Lasse Espeholt

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 17

Top Topics

Image Generation

Reinforcement Learning

Meta Search Engine

Top Venues

Publications

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