beta-vae: Learning basic visual concepts with a constrained variational framework. I Higgins, L Matthey, A Pal, CP Burgess, X Glorot, MM Botvinick, ...
ICLR (Poster) 3, 2017
4902 2017 Understanding disentangling in CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ...
arXiv preprint arXiv:1804.03599, 2018
1103 2018 Scaling language models: Methods, analysis & insights from training gopher JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
arXiv preprint arXiv:2112.11446, 2021
743 2021 Monet: Unsupervised scene decomposition and representation CP Burgess, L Matthey, N Watters, R Kabra, I Higgins, M Botvinick, ...
arXiv preprint arXiv:1901.11390, 2019
493 2019 Towards a definition of disentangled representations I Higgins, D Amos, D Pfau, S Racaniere, L Matthey, D Rezende, ...
arXiv preprint arXiv:1812.02230, 2018
488 2018 Darla: Improving zero-shot transfer in reinforcement learning I Higgins, A Pal, A Rusu, L Matthey, C Burgess, A Pritzel, M Botvinick, ...
International Conference on Machine Learning, 1480-1490, 2017
485 2017 dSprites - Disentanglement testing Sprites dataset L Matthey, I Higgins, D Hassabis, A Lercher
https://github.com/deepmind/dsprites-dataset, 2017
392 2017 Hamiltonian generative networks P Toth, DJ Rezende, A Jaegle, S Racanière, A Botev, I Higgins
arXiv preprint arXiv:1909.13789, 2019
208 2019 Selection-inference: Exploiting large language models for interpretable logical reasoning A Creswell, M Shanahan, I Higgins
arXiv preprint arXiv:2205.09712, 2022
203 2022 Scan: Learning hierarchical compositional visual concepts I Higgins, N Sonnerat, L Matthey, A Pal, CP Burgess, M Bosnjak, ...
arXiv preprint arXiv:1707.03389, 2017
160 2017 International Conference on Learning Representations I Higgins, L Matthey, A Pal, C Burgess, X Glorot, M Botvinick, S Mohamed, ...
ICLR 2017, Toulon, France, 2017
147 2017 Life-long disentangled representation learning with cross-domain latent homologies A Achille, T Eccles, L Matthey, C Burgess, N Watters, A Lerchner, ...
Advances in Neural Information Processing Systems 31, 2018
134 2018 Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons I Higgins, L Chang, V Langston, D Hassabis, C Summerfield, D Tsao, ...
Nature communications 12 (1), 6456, 2021
120 2021 Cyprien de Masson d’Autume JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
80 2021 Unsupervised Model Selection for Variational Disentangled Representation Learning S Duan, L Matthey, A Saraiva, N Watters, CP Burgess, A Lerchner, ...
arXiv preprint arXiv:1905.12614, 2019
77 2019 Solving math word problems with process-and outcome-based feedback J Uesato, N Kushman, R Kumar, F Song, N Siegel, L Wang, A Creswell, ...
arXiv preprint arXiv:2211.14275, 2022
70 2022 Equivariant hamiltonian flows DJ Rezende, S Racanière, I Higgins, P Toth
arXiv preprint arXiv:1909.13739, 2019
60 2019 Understanding disentangling in β CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ...
arXiv preprint arXiv:1804.03599, 2018
51 2018 Cyprien de Masson d’Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, HF Song, J Aslanides, ...
Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William S. Isaac …, 2021
47 2021 Symmetry-based representations for artificial and biological general intelligence I Higgins, S Racanière, D Rezende
Frontiers in Computational Neuroscience 16, 836498, 2022
40 2022 
Loic MattheyDeepMindПодтвержден адрес электронной почты в домене google.com
