Tom Le Paine
Tom Le Paine
Research Scientist, DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Alphastar: Mastering the real-time strategy game starcraft ii
O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, ...
DeepMind blog, 2, 2019
1812019
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
1662015
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
1362019
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
1192010
Seq-nms for video object detection
W Han, P Khorrami, TL Paine, P Ramachandran, M Babaeizadeh, H Shi, ...
arXiv preprint arXiv:1602.08465, 2016
1072016
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
942018
Fast generation for convolutional autoregressive models
P Ramachandran, TL Paine, P Khorrami, M Babaeizadeh, S Chang, ...
arXiv preprint arXiv:1704.06001, 2017
88*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
772013
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
632016
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
432014
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
382017
Large-scale visual speech recognition
B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ...
arXiv preprint arXiv:1807.05162, 2018
352018
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
172011
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
112016
Oord
S Reed, Y Chen, T Paine
A. vd, Kalchbrenner, N., Colmenarejo, SG, Wang, Z., Belov, D., and de Freitas, 2017
102017
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
92018
Visual Media: History and Perspectives
T Huang, V Le, TL Paine, P Khorrami, U Tariq
MultiMedia, IEEE 21 (2), 4-10, 2014
62014
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
32019
Leakage corrected rCBV measurements using prebolus dosing: applications in differentiating glioma recurrence from post-treatment effect at 3T field strength—
LS Hu, LC Baxter, TL Paine, JP Karis, BG Feuerstein, S Beeman, ...
Proceedings of the International Society for Magnetic Resonance in Medicine, 3-9, 2008
32008
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
22017
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