Jimmy Ba
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Adam: A method for stochastic optimization
D Kingma, J Ba
International Conference on Learning Representations, 2015
577152015
Show, attend and tell: Neural image caption generation with visual attention
K Xu, J Ba, R Kiros, K Cho, A Courville, R Salakhudinov, R Zemel, ...
International conference on machine learning, 2048-2057, 2015
59242015
Layer normalization
J Ba, JR Kiros, GE Hinton
Advances in NIPS 2016 Deep Learning Symposium, arXiv preprint arXiv:1607.06450, 2016
23332016
Do deep nets really need to be deep?
J Ba, R Caruana
Advances in neural information processing systems, 2654-2662, 2014
12222014
Multiple object recognition with visual attention
J Ba, V Mnih, K Kavukcuoglu
International Conference on Learning Representations, 2015
7532015
Scalable trust-region method for deep reinforcement learning using kronecker-factored approximation
Y Wu, E Mansimov, RB Grosse, S Liao, J Ba
Advances in neural information processing systems, 5279-5288, 2017
3432017
Actor-mimic: Deep multitask and transfer reinforcement learning
E Parisotto, J Ba, R Salakhutdinov
International Conference on Learning Representations, arXiv preprint arXiv …, 2016
3142016
Predicting deep zero-shot convolutional neural networks using textual descriptions
J Ba, K Swersky, S Fidler
Proceedings of the IEEE International Conference on Computer Vision, 4247-4255, 2015
2892015
Generating images from captions with attention
E Mansimov, E Parisotto, J Ba, R Salakhutdinov
International Conference on Learning Representations, arXiv preprint arXiv …, 2016
2432016
Classifying and segmenting microscopy images with deep multiple instance learning
OZ Kraus, JL Ba, BJ Frey
Bioinformatics 32 (12), i52-i59, 2016
2392016
Adaptive dropout for training deep neural networks
J Ba, B Frey
Advances in neural information processing systems, 3084-3092, 2013
2362013
Automated analysis of high‐content microscopy data with deep learning
OZ Kraus, BT Grys, J Ba, Y Chong, BJ Frey, C Boone, BJ Andrews
Molecular systems biology 13 (4), 924, 2017
1462017
Using fast weights to attend to the recent past
J Ba, GE Hinton, V Mnih, JZ Leibo, C Ionescu
Advances in Neural Information Processing Systems, 4331-4339, 2016
1082016
Lookahead Optimizer: k steps forward, 1 step back
M Zhang, J Lucas, GE Hinton, J Ba
Advances in Neural Information Processing Systems, 9593-9604, 2019
1042019
Benchmarking Model-Based Reinforcement Learning
T Wang, X Bao, I Clavera, J Hoang, Y Wen, E Langlois, S Zhang, G Zhang, ...
arXiv preprint arXiv:1907.02057, 2019
85*2019
Adam: A method for stochastic gradient descent
DP Kingma, JL Ba
ICLR: International Conference on Learning Representations, 2015
732015
Adam: a method for stochastic optimization, 1–15
DP Kingma, J Ba
arXiv preprint arXiv:1412.6980, 2014
71*2014
Nervenet: Learning structured policy with graph neural networks
T Wang, R Liao, J Ba, S Fidler
International Conference on Learning Representations, 2018
702018
Flipout: Efficient pseudo-independent weight perturbations on mini-batches
Y Wen, P Vicol, J Ba, D Tran, R Grosse
International Conference on Learning Representations, 2018
662018
Adam: a method for stochastic optimization. CoRR
DP Kingma, J Ba
arXiv preprint arXiv:1412.6980, 2014
632014
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