Jacob Menick
Jacob Menick
Verifierad e-postadress på google.com
Citeras av
Citeras av
Noisy networks for exploration
M Fortunato, MG Azar, B Piot, J Menick, I Osband, A Graves, V Mnih, ...
arXiv preprint arXiv:1706.10295, 2017
Automated curriculum learning for neural networks
A Graves, MG Bellemare, J Menick, R Munos, K Kavukcuoglu
international conference on machine learning, 1311-1320, 2017
Rigging the lottery: Making all tickets winners
U Evci, T Gale, J Menick, PS Castro, E Elsen
International Conference on Machine Learning, 2943-2952, 2020
Generating high fidelity images with subscale pixel networks and multidimensional upscaling
J Menick, N Kalchbrenner
arXiv preprint arXiv:1812.01608, 2018
Multiplicative interactions and where to find them
SM Jayakumar, WM Czarnecki, J Menick, J Schwarz, J Rae, S Osindero, ...
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
Multimodal few-shot learning with frozen language models
M Tsimpoukelli, JL Menick, S Cabi, SM Eslami, O Vinyals, F Hill
Advances in Neural Information Processing Systems 34, 200-212, 2021
Improving language models by retrieving from trillions of tokens
S Borgeaud, A Mensch, J Hoffmann, T Cai, E Rutherford, K Millican, ...
arXiv preprint arXiv:2112.04426, 2021
Noisy networks for exploration. arXiv 2017
M Fortunato, MG Azar, B Piot, J Menick, I Osband, A Graves, V Mnih, ...
arXiv preprint arXiv:1706.10295, 0
Generating images with sparse representations
C Nash, J Menick, S Dieleman, PW Battaglia
arXiv preprint arXiv:2103.03841, 2021
Associative compression networks for representation learning
A Graves, J Menick, A Oord
arXiv preprint arXiv:1804.02476, 2018
Associative compression networks
A Graves, J Menick, A van den Oord
arXiv preprint arXiv:1804.02476, 2018
A practical sparse approximation for real time recurrent learning
J Menick, E Elsen, U Evci, S Osindero, K Simonyan, A Graves
arXiv preprint arXiv:2006.07232, 2020
Flamingo: a visual language model for few-shot learning
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
arXiv preprint arXiv:2204.14198, 2022
Teaching language models to support answers with verified quotes
J Menick, M Trebacz, V Mikulik, J Aslanides, F Song, M Chadwick, ...
arXiv preprint arXiv:2203.11147, 2022
Practical real time recurrent learning with a sparse approximation
J Menick, E Elsen, U Evci, S Osindero, K Simonyan, A Graves
International Conference on Learning Representations, 2020
Data compression using jointly trained encoder, decoder, and prior neural networks
JL Menick, AB Graves
US Patent App. 16/767,010, 2021
Reduced computation real time recurrent learning
JL Menick, EK Elsen, K Simonyan
US Patent App. 17/169,083, 2021
Training machine learning models using task selection policies to increase learning progress
M Gendron-Bellemare, JL Menick, AB Graves, K Kavukcuoglu, R Munos
US Patent App. 17/159,961, 2021
Noisy neural network layers with noise parameters
MG Azar, M Fortunato, B Piot, OC Pietquin, JL Menick, V Mnih, C Blundell, ...
US Patent App. 17/020,248, 2021
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20