Siddhant M. Jayakumar
Siddhant M. Jayakumar
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Cited by
Cited by
Compressive transformers for long-range sequence modelling
JW Rae, A Potapenko, SM Jayakumar, TP Lillicrap
arXiv preprint arXiv:1911.05507, 2019
Memory-based parameter adaptation
P Sprechmann, SM Jayakumar, JW Rae, A Pritzel, AP Badia, B Uria, ...
ICLR 2018, 2018
Adapting auxiliary losses using gradient similarity
Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ...
arXiv preprint arXiv:1812.02224, 2018
Been there, done that: Meta-learning with episodic recall
S Ritter, JX Wang, Z Kurth-Nelson, SM Jayakumar, C Blundell, R Pascanu, ...
ICML 2018, 2018
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
Mix&match-agent curricula for reinforcement learning
WM Czarnecki, SM Jayakumar, M Jaderberg, L Hasenclever, YW Teh, ...
ICML 2018, 2018
Stabilizing transformers for reinforcement learning
E Parisotto, F Song, J Rae, R Pascanu, C Gulcehre, S Jayakumar, ...
International Conference on Machine Learning, 7487-7498, 2020
Distilling Policy Distillation
WM Czarnecki, R Pascanu, S Osindero, SM Jayakumar, G Swirszcz, ...
AISTATS 2019, 2019
Information asymmetry in KL-regularized RL
A Galashov, SM Jayakumar, L Hasenclever, D Tirumala, J Schwarz, ...
ICLR 2019, 2019
Multiplicative interactions and where to find them
SM Jayakumar, WM Czarnecki, J Menick, J Schwarz, J Rae, S Osindero, ...
International Conference on Learning Representations, 2020
Top-KAST: Top-K Always Sparse Training
S Jayakumar, R Pascanu, J Rae, S Osindero, E Elsen
Advances in Neural Information Processing Systems 33, 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
Perception-Prediction-Reaction Agents for Deep Reinforcement Learning
A Stooke, V Dalibard, SM Jayakumar, WM Czarnecki, M Jaderberg
Workshop on “Structure & Priors in Reinforcement Learning” at ICLR 2019, 2019
Machine learning systems with memory based parameter adaptation for learning fast and slower
P Sprechmann, S Jayakumar, JW Rae, A Pritzel, AP Badia, O Vinyals, ...
US Patent App. 16/759,561, 2020
Reinforcement learning using agent curricula
W Czarnecki, S Jayakumar
US Patent App. 16/417,522, 2019
Information asymmetry in KL-regularized RL
WM Czarnecki, L Hasenclever, YW Teh, G Desjardins, A Galashov, ...
International Conference on Learning Representations, 2018
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