新论文：最近6个月以内的 Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models, S. Ioffe. Wasserstein GAN, M. Arjovsky et al. Understanding deep learning requires rethinking generalization, C. Zhang et al. [pdf] 老论文：2012年以前的 An
Layer Normalization (2016), J. Ba et al. Learning to learn by gradient descent by gradient descent (2016), M. Andrychowicz et al. Domain-adversarial training of neural networks (2016), Y. Ganin et al. WaveNet: A Generative Model for Raw Audio (2016)
深度学习工具包 Deprecation notice. ----- This toolbox is outdated and no longer maintained. There are much better tools available for deep learning than this toolbox, e.g. [Theano](http://deeplearning.net/software/theano/), [torch](http://torch.ch/) or [te
通过深度学习增强的视网膜光学相干断层扫描图像论文，pdf格式Research Article
VoL 9, No 12 1 Dec 2018 BIOMEDICAL OPTICS EXPRESS 6207
Biomedical Optics EXPRESS
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To achieve this we train a generator network as a feed-forward convolutional neural network
(CNN) GeG par
Non-intrusive inspection systerms based on X-ray radiography techriques are rou tinely used at transport hubs to ensure the conforrmity of catgo content with the supplied shipping manifest. As trade volurmes increase and regulatiors become more strin
深度学习的起源.pdfON THE ORIGIN OF DEEP LEARNING
Table 1: Major milestones that will be covered in this paper
Year
Contributer
Contribution
300BC
Aristotle
introduced Associationism, started the history of human's
attempt to understand brain
1873
Alexander
