Deep Learning, Yoshua Bengio, Ian Goodfellow, Aaron Courville, MIT Press

Gradient-Based Learning Applied to Document Recognition, Yann Lecun, 1998

Dropout: A Simple Way to Prevent Neural Networks from Overfitting, Srivastava et al. 2014

Greedy layer-wise training of deep networks, Bengio, Yoshua, et al. Advances in neural information processing systems 19 (2007): 153.

Reducing the dimensionality of data with neural networks, Hinton et al. Science 313.5786 (2006): 504-507.

Training Deep and Recurrent Neural Networks with Hessian-Free Optimization, James Martens and Ilya Sutskever, Neural Networks: Tricks of the Trade, 2012.

Deep boltzmann machines, Hinton et al.

Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion, Pascal Vincent et al.

A fast learning algorithm for deep belief nets, Hinton et al., 2006

ImageNet Classification with Deep Convolutional Neural Networks, Alex Krizhevsky, Ilya Sutskever, Geoffrey E Hinton, NIPS 2012

Regularization of Neural Networks using DropConnect, Wan et al., ICML

OverFeat: Integrated recognition, localization and detection using convolutional networks. Computing Research Repository, abs/1312.6229, 2013.

http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial

http://deeplearning.net/tutorial/

Deep Learning Course on Coursera by Hinton

DL platform with GPU support: caffe, lasagne, torch etc.