Tom Le Paine
Tom Le Paine
Research Scientist, DeepMind
Verified email at - Homepage
Cited by
Cited by
Grandmaster level in StarCraft II using multi-agent reinforcement learning
O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ...
Nature 575 (7782), 350-354, 2019
Alphastar: Mastering the real-time strategy game starcraft ii
O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, ...
DeepMind blog, 2, 2019
Do deep neural networks learn facial action units when doing expression recognition?
P Khorrami, T Paine, T Huang
Proceedings of the IEEE International Conference on Computer Vision …, 2015
Seq-nms for video object detection
W Han*, P Khorrami*, TL Paine*, P Ramachandran, M Babaeizadeh, ...
arXiv preprint arXiv:1602.08465, 2016
Playing hard exploration games by watching youtube
Y Aytar, T Pfaff, D Budden, T Paine, Z Wang, N de Freitas
Advances in Neural Information Processing Systems, 2930-2941, 2018
Optimized preload leakage-correction methods to improve the diagnostic accuracy of dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in posttreatment gliomas
LS Hu, LC Baxter, DS Pinnaduwage, TL Paine, JP Karis, BG Feuerstein, ...
American Journal of Neuroradiology 31 (1), 40-48, 2010
Fast generation for convolutional autoregressive models
P Ramachandran*, TL Paine*, P Khorrami, M Babaeizadeh, S Chang, ...
arXiv preprint arXiv:1704.06001, 2017
GPU asynchronous stochastic gradient descent to speed up neural network training
TL Paine, H Jin, J Yang, Z Lin, T Huang
arXiv preprint arXiv:1312.6186, 2013
How deep neural networks can improve emotion recognition on video data
P Khorrami, T Le Paine, K Brady, C Dagli, TS Huang
2016 IEEE international conference on image processing (ICIP), 619-623, 2016
An analysis of unsupervised pre-training in light of recent advances
TL Paine*, P Khorrami*, W Han, TS Huang
arXiv preprint arXiv:1412.6597, 2014
Few-shot autoregressive density estimation: Towards learning to learn distributions
S Reed, Y Chen, T Paine, A Oord, SM Eslami, D Rezende, O Vinyals, ...
arXiv preprint arXiv:1710.10304, 2017
Large-scale visual speech recognition
B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ...
arXiv preprint arXiv:1807.05162, 2018
Simultaneous dynamic and functional MRI scanning (SimulScan) of natural swallows
TL Paine, CA Conway, GA Malandraki, BP Sutton
Magnetic Resonance in Medicine 65 (5), 1247-1252, 2011
Image classification using images with separate grayscale and color channels
H Jin, T Le Paine, J Yang, Z Lin, JW Brandt
US Patent 9,230,192, 2016
S Reed, Y Chen, T Paine
A. vd, Kalchbrenner, N., Colmenarejo, SG, Wang, Z., Belov, D., and de Freitas, 2017
One-shot high-fidelity imitation: Training large-scale deep nets with rl
TL Paine*, SG Colmenarejo*, Z Wang, S Reed, Y Aytar, T Pfaff, ...
arXiv preprint arXiv:1810.05017, 2018
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
Visual Media: History and Perspectives
T Huang, V Le, TL Paine, P Khorrami, U Tariq
MultiMedia, IEEE 21 (2), 4-10, 2014
Acme: A Research Framework for Distributed Reinforcement Learning
M Hoffman, B Shahriari, J Aslanides, G Barth-Maron, F Behbahani, ...
arXiv preprint arXiv:2006.00979, 2020
Magnetic susceptibility‐induced echo‐time shifts: Is there a bias in age‐related fMRI studies?
GC Ngo, CN Wong, S Guo, T Paine, AF Kramer, BP Sutton
Journal of Magnetic Resonance Imaging 45 (1), 207-214, 2017
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