| Teaching machines to read and comprehend KM Hermann, T Kocisky, E Grefenstette, L Espeholt, W Kay, M Suleyman, ... Advances in neural information processing systems 28, 1693-1701, 2015 | 1948 | 2015 |
| Conditional image generation with pixelcnn decoders A Van den Oord, N Kalchbrenner, L Espeholt, O Vinyals, A Graves Advances in neural information processing systems 29, 4790-4798, 2016 | 1223 | 2016 |
| Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures L Espeholt, H Soyer, R Munos, K Simonyan, V Mnih, T Ward, Y Doron, ... arXiv preprint arXiv:1802.01561, 2018 | 525 | 2018 |
| Neural machine translation in linear time N Kalchbrenner, L Espeholt, K Simonyan, A Oord, A Graves, ... arXiv preprint arXiv:1610.10099, 2016 | 370 | 2016 |
| Multi-task deep reinforcement learning with popart M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H van Hasselt Proceedings of the AAAI Conference on Artificial Intelligence 33, 3796-3803, 2019 | 75 | 2019 |
| Processing sequences using convolutional neural networks AGA van den Oord, SEL Dieleman, NE Kalchbrenner, K Simonyan, ... US Patent App. 15/697,407, 2018 | 23 | 2018 |
| Google research football: A novel reinforcement learning environment K Kurach, A Raichuk, P Stańczyk, M Zając, O Bachem, L Espeholt, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4501-4510, 2020 | 22 | 2020 |
| SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference L Espeholt, R Marinier, P Stanczyk, K Wang, M Michalski arXiv preprint arXiv:1910.06591, 2019 | 20 | 2019 |
| Reading comprehension neural networks KM Hermann, T Kocisky, ET Grefenstette, L Espeholt, WT Kay, ... US Patent 10,628,735, 2020 | 15 | 2020 |
| MetNet: A Neural Weather Model for Precipitation Forecasting CK Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ... arXiv preprint arXiv:2003.12140, 2020 | 13 | 2020 |
| Conditional image generation with PixelCNN decoders N Kalchbrenner, L Espeholt, O Vinyals, A Graves Advances in Neural Information Processing Systems, 2016 | 9 | 2016 |
| Processing text sequences using neural networks NE Kalchbrenner, K Simonyan, L Espeholt US Patent 10,354,015, 2019 | 6 | 2019 |
| Method for modeling source code having code segments that lack source location J Van Gogh, SF Yegge, MJ Fromberger, A Shali, GS West, JA Dennett, ... US Patent 9,116,780, 2015 | 5 | 2015 |
| Speech recognition using convolutional neural networks AGA van den Oord, SEL Dieleman, NE Kalchbrenner, K Simonyan, ... US Patent 10,586,531, 2020 | 2 | 2020 |
| Google Research Football: A Novel Reinforcement Learning Environment A Raichuk, C Riquelme, D Vincent, K Kurach, L Espeholt, M Michalski, ... | 1 | 2019 |
| Processing text sequences using neural networks NE Kalchbrenner, K Simonyan, L Espeholt US Patent App. 16/927,267, 2020 | | 2020 |
| SPEECH RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS OAGA Van Den, SEL Dieleman, NE Kalchbrenner, K Simonyan, O Vinyals, ... US Patent App. 16/719,424, 2020 | | 2020 |
| MetNet: A Neural Weather Model for Precipitation Forecasting C Kaae Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ... arXiv, arXiv: 2003.12140, 2020 | | 2020 |
Nal KalchbrennerGoogle Brain AmsterdamVerified email at google.com
