Progressive neural networks AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ... arXiv preprint arXiv:1606.04671, 2016 | 2948 | 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, ... International conference on machine learning, 1407-1416, 2018 | 1617 | 2018 |
Learning to reinforcement learn JX Wang, Z Kurth-Nelson, D Tirumala, H Soyer, JZ Leibo, R Munos, ... arXiv preprint arXiv:1611.05763, 2016 | 1076 | 2016 |
Learning to navigate in complex environments P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ... arXiv preprint arXiv:1611.03673, 2016 | 974 | 2016 |
Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018 | 722 | 2018 |
Prefrontal cortex as a meta-reinforcement learning system JX Wang, Z Kurth-Nelson, D Kumaran, D Tirumala, H Soyer, JZ Leibo, ... Nature neuroscience 21 (6), 860-868, 2018 | 637 | 2018 |
Grounded Language Learning in a Simulated 3D World KM Hermann, F Hill, S Green, F Wang, R Faulkner, H Soyer, D Szepesvari, ... CoRR, abs/1706.06551, 2017 | 340* | 2017 |
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 | 306 | 2019 |
V-mpo: On-policy maximum a posteriori policy optimization for discrete and continuous control HF Song, A Abdolmaleki, JT Springenberg, A Clark, H Soyer, JW Rae, ... arXiv preprint arXiv:1909.12238, 2019 | 115 | 2019 |
Image super-resolution with fast approximate convolutional sparse coding C Osendorfer, H Soyer, P Van Der Smagt Neural Information Processing: 21st International Conference, ICONIP 2014 …, 2014 | 97 | 2014 |
Making efficient use of demonstrations to solve hard exploration problems TL Paine, C Gulcehre, B Shahriari, M Denil, M Hoffman, H Soyer, ... arXiv preprint arXiv:1909.01387, 2019 | 93 | 2019 |
Leveraging monolingual data for crosslingual compositional word representations H Soyer, P Stenetorp, A Aizawa arXiv preprint arXiv:1412.6334, 2014 | 37 | 2014 |
Size (and domain) matters: Evaluating semantic word space representations for biomedical text P Stenetorp, H Soyer, S Pyysalo, S Ananiadou, T Chikayama Proceedings of SMBM 12, 2012 | 30 | 2012 |
Uncovering surprising behaviors in reinforcement learning via worst-case analysis A Ruderman, R Everett, B Sikder, H Soyer, J Uesato, A Kumar, C Beattie, ... | 13 | 2019 |
Scaling instructable agents across many simulated worlds M Abi Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton, B Brownfield, ... arXiv e-prints, arXiv: 2404.10179, 2024 | 6* | 2024 |
Environment navigation using reinforcement learning F Viola, PW Mirowski, A Banino, R Pascanu, HJ Soyer, AJ Ballard, ... US Patent 10,572,776, 2020 | 6 | 2020 |
Low-pass recurrent neural networks-a memory architecture for longer-term correlation discovery T Stepleton, R Pascanu, W Dabney, SM Jayakumar, H Soyer, R Munos arXiv preprint arXiv:1805.04955, 2018 | 5 | 2018 |
Crovewa: Crosslingual vector-based writing assistance H Soyer, G Topić, P Stenetorp, A Aizawa Proceedings of the 2015 Conference of the North American Chapter of the …, 2015 | 5 | 2015 |
Japanese to english machine translation using preordering and compositional distributed semantics S Hoshino, H Soyer, Y Miyao, A Aizawa Proceedings of the 1st Workshop on Asian Translation (WAT2014), 55-63, 2014 | 5 | 2014 |
Distributed training using actor-critic reinforcement learning with off-policy correction factors HJ Soyer, L Espeholt, K Simonyan, Y Doron, V Firoiu, V Mnih, ... US Patent App. 18/487,428, 2024 | | 2024 |