| Reinforcement learning with unsupervised auxiliary tasks M Jaderberg*, V Mnih*, WM Czarnecki*, T Schaul, JZ Leibo, D Silver, ... ICLR 2017, 2017 | 641 | 2017 |
| Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals*, I Babuschkin*, WM Czarnecki*, M Mathieu*, A Dudzik*, ... Nature, 1-5, 2019 | 591* | 2019 |
| On loss functions for deep neural networks in classification K Janocha, WM Czarnecki TFML 2017, 2017 | 274 | 2017 |
| Population based training of neural networks M Jaderberg, V Dalibard, S Osindero, WM Czarnecki, J Donahue, ... arXiv preprint arXiv:1711.09846, 2017 | 262 | 2017 |
| Human-level performance in 3D multiplayer games with population-based reinforcement learning M Jaderberg*, WM Czarnecki*, I Dunning*, L Marris, G Lever, ... Science 364 (6443), 859-865, 2019 | 257 | 2019 |
| Distral: Robust Multitask Reinforcement Learning YW Teh, V Bapst, WM Czarnecki, J Quan, J Kirkpatrick, R Hadsell, ... NIPS 2017, 2017 | 224 | 2017 |
| Value-decomposition networks for cooperative multi-agent learning P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ... AAMAS 2018, 2017 | 199* | 2017 |
| Decoupled neural interfaces using synthetic gradients M Jaderberg, WM Czarnecki, S Osindero, O Vinyals, A Graves, ... ICML 2017, 2017 | 192 | 2017 |
| Progress & Compress: A scalable framework for continual learning J Schwarz, J Luketina, WM Czarnecki, A Grabska-Barwinska, YW Teh, ... ICML 2018, 2018 | 183 | 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 | 135* | 2017 |
| Sobolev Training for Neural Networks WM Czarnecki, S Osindero, M Jaderberg, G Świrszcz, R Pascanu NIPS 2017, 2017 | 70 | 2017 |
| Multi-task deep reinforcement learning with popart M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H van Hasselt AAAI 2019, 2018 | 65 | 2018 |
| Local minima in training of neural networks G Swirszcz, WM Czarnecki, R Pascanu arXiv preprint arXiv:1611.06310, 2016 | 58* | 2016 |
| How to evaluate word embeddings? on importance of data efficiency and simple supervised tasks S Jastrzebski, D Leśniak, WM Czarnecki arXiv preprint arXiv:1702.02170, 2017 | 47 | 2017 |
| Learning to SMILE (s) S Jastrzebski, D Lesniak, WM Czarnecki ICLR 2016 Workshop track, 2016 | 45* | 2016 |
| Kickstarting Deep Reinforcement Learning S Schmitt, JJ Hudson, A Zidek, S Osindero, C Doersch, WM Czarnecki, ... NIPS 2018 DL Workshop, 2018 | 43 | 2018 |
| Adapting auxiliary losses using gradient similarity Y Du, WM Czarnecki, SM Jayakumar, R Pascanu, B Lakshminarayanan NeurIPS 2018 MetaLearning Workshop, 2018 | 37 | 2018 |
| Understanding Synthetic Gradients and Decoupled Neural Interfaces WM Czarnecki, G Świrszcz, M Jaderberg, S Osindero, O Vinyals, ... ICML 2017, 2017 | 34 | 2017 |
| Weighted tanimoto extreme learning machine with case study in drug discovery WM Czarnecki IEEE Computational Intelligence Magazine 10 (3), 19-29, 2015 | 31 | 2015 |
| Robust optimization of SVM hyperparameters in the classification of bioactive compounds WM Czarnecki, S Podlewska, A Bojarski Journal of Cheminformatics 7 (38), 2015 | 30 | 2015 |
Max JaderbergDeepMindAdresse e-mail validée de robots.ox.ac.uk
