Jimmy Ba
Jimmy Ba
在 cs.toronto.edu 的電子郵件地址已通過驗證 - 首頁
標題
引用次數
引用次數
年份
Adam: A method for stochastic optimization
D Kingma, J Ba
International Conference on Learning Representations, 2015
570642015
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
58872015
Layer normalization
J Ba, JR Kiros, GE Hinton
Advances in NIPS 2016 Deep Learning Symposium, arXiv preprint arXiv:1607.06450, 2016
22922016
Do deep nets really need to be deep?
J Ba, R Caruana
Advances in neural information processing systems, 2654-2662, 2014
12152014
Multiple object recognition with visual attention
J Ba, V Mnih, K Kavukcuoglu
International Conference on Learning Representations, 2015
7492015
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
3392017
Actor-mimic: Deep multitask and transfer reinforcement learning
E Parisotto, J Ba, R Salakhutdinov
International Conference on Learning Representations, arXiv preprint arXiv …, 2016
3132016
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
2872015
Generating images from captions with attention
E Mansimov, E Parisotto, J Ba, R Salakhutdinov
International Conference on Learning Representations, arXiv preprint arXiv …, 2016
2422016
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
2332013
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
1432017
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
1062016
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
972019
Adam: a method for stochastic optimization, 1–15
DP Kingma, J Ba
arXiv preprint arXiv:1412.6980, 2014
92*2014
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
82*2019
Nervenet: Learning structured policy with graph neural networks
T Wang, R Liao, J Ba, S Fidler
International Conference on Learning Representations, 2018
702018
Adam: A method for stochastic gradient descent
DP Kingma, JL Ba
ICLR: International Conference on Learning Representations, 2015
682015
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
642018
Adam: a method for stochastic optimization. CoRR
DP Kingma, J Ba
arXiv preprint arXiv:1412.6980, 2014
632014
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