The Brain vs Deep Learning Part I: Computational Complexity — Or Why the Singularity Is Nowhere Near | Deep LearningO网页链接

【视频:(RLDM 2015)David Silver的深度强化学习教程】《Tutorial on "Deep Reinforcement Learning"》 by David Silver at RLDM 2015O网页链接

【视频:(RLDM 2015)计算强化学习入门】《Basics of Computational Reinforcement Learning》 by Michael Littman at RLDM 2015O网页链接

"On Explainability of Deep Neural Networks"On Explainability of Deep Neural Networks，深度神经网络的可解释性O网页链接  On Explainability of Deep Neural Networks，深度神经网络的可解释性O网页链接

【开源:基于variational autoencoders (VAEs)的"渐变脸"】"Morphing Faces"O网页链接Demo:O网页链接GitHub:O网页链接

【"Deep Learning for NLP: progress, challenges and opportunities"】经过报告人同意，7月30日晚@鲁东东胖在清华的报告《Deep Learning for NLP@Noah: progress, challenges and opportunities》演示文稿可以在此下载：OTsinghuaTalkJ_July30.pdf感谢正东的精彩报告，感谢到场的同学们。:)

【幻灯:(nVIDIA深度学习课程)GPU深度学习介绍】《Introduction To Deep Learning With GPUs》O网页链接云:O网页链接

【论文:"NoBackTrack" RNN】《Training recurrent networks online without backtracking》Y Ollivier, G Charpiat (2015)O网页链接

【论文:深度学习模型演进】《Evolution of Deep learning models》 Ajit Jaokar (2015)O网页链接pdf:O网页链接

【论文+代码:面向图像分类的多列深度网络(MCDNN)】《Multi-column Deep Neural Networks for Image Classification》D Cireşan, U Meier, J Schmidhuber (CVPR2012)O网页链接Code(Theano):O网页链接

【(Python)三行代码实现Hinton's Dropout】《Hinton's Dropout in 3 Lines of Python - How to install Dropout into a neural network by only changing 3 lines of python》by TraskO网页链接

【视频:深度学习并行训练算法浅析】@InfoQ发布的《如何让机器学习得更快——深度学习并行训练算法浅析》by 鹿晓亮O网页链接

【视频:Hinton在Cambridge介绍深度学习及其最新进展的报告】《(Cambridge)Deep Learning: Professor Geoffrey Hinton FRS, 25 June 2015》O网页链接云:O网页链接

【视频:Hinton在Cambridge介绍深度学习及其最新进展的报告】《(Cambridge)Deep Learning: Professor Geoffrey Hinton FRS, 25 June 2015》O网页链接讲座给我的感觉：ReLU+dropout+反向传播基本实现了神经系统中信号传播和学习方法的精髓，后面重点在网络体系结构，和更多的数据及计算能力。不知道Hinton是不是真有这么乐观。

【视频:David Silver(DeeMind)的强化学习课程】《Reinforcement Learning course by DeeMind's David Silver》O网页链接云:O网页链接Slides&Info:O网页链接Clip.mn标注的版本：O网页链接