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Lasse Espeholt
Lasse Espeholt
Google Brain Amsterdam
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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, 2015
41332015
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, 2016
29162016
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, ...
International conference on machine learning, 1407-1416, 2018
17242018
Neural machine translation in linear time
N Kalchbrenner
arXiv preprint arXiv:1610.10099, 2016
7152016
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
4102020
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
3342020
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 (01), 3796-3803, 2019
3242019
Deep learning for twelve hour precipitation forecasts
L Espeholt, S Agrawal, C Sønderby, M Kumar, J Heek, C Bromberg, ...
Nature communications 13 (1), 1-10, 2022
2232022
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
1502019
Processing sequences using convolutional neural networks
AGA van den Oord, SEL Dieleman, NE Kalchbrenner, K Simonyan, ...
US Patent 11,080,591, 2021
802021
k. kavukcuoglu, O
A van den Oord, N Kalchbrenner, L Espeholt
Neural discrete representation learning,” in Advances in Neural Information …, 2017
65*2017
Deep learning for day forecasts from sparse observations
M Andrychowicz, L Espeholt, D Li, S Merchant, A Merose, F Zyda, ...
arXiv preprint arXiv:2306.06079, 2023
432023
Processing text sequences using neural networks
NE Kalchbrenner, K Simonyan, L Espeholt
US Patent 10,354,015, 2019
322019
Boosting search engines with interactive agents
L Adolphs, B Boerschinger, C Buck, MC Huebscher, M Ciaramita, ...
arXiv preprint arXiv:2109.00527, 2021
252021
Reading comprehension neural networks
KM Hermann, T Kocisky, ET Grefenstette, L Espeholt, WT Kay, ...
US Patent 10,628,735, 2020
252020
Speech recognition using convolutional neural networks
AGA van den Oord, SEL Dieleman, NE Kalchbrenner, K Simonyan, ...
US Patent 10,586,531, 2020
172020
Agent-centric representations for multi-agent reinforcement learning
W Shang, L Espeholt, A Raichuk, T Salimans
arXiv preprint arXiv:2104.09402, 2021
122021
Skillful twelve hour precipitation forecasts using large context neural networks. arXiv 2021
L Espeholt, S Agrawal, C Sønderby, M Kumar, J Heek, C Bromberg, ...
arXiv preprint arXiv:2111.07470, 0
10
Processing text sequences using neural networks
NE Kalchbrenner, K Simonyan, L Espeholt
US Patent 11,321,542, 2022
72022
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
72015
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