• DBN: Deep Belief Nets

• CDBN: Deep Belief Nets w/ continuous-valued inputs

• RBM: Restricted Boltzmann Machine

• CRBM: Restricted Boltzmann Machine w/ continuous-valued inputs

• dA: Denoising Autoencoders

• SdA: Stacked Denoising Autoencoders

• LogisticRegression: Logistic Regression

• HiddenLayer: Hidden Layer of Neural Networks

• MLP: Multiple Layer Perceptron

• Dropout: Dropout MLP

• CNN: Convolutional Neural Networks (See dev branch.)

• Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle: Greedy Layer-Wise Training of Deep Networks, Advances in Neural Information Processing Systems 19, 2007

• P. Vincent, H. Larochelle, Y. Bengio, P.A. Manzagol: Extracting and Composing Robust Features with Denoising Autoencoders, ICML' 08, 1096-1103, 2008

• DeepLearningTutorials https://github.com/lisa-lab/DeepLearningTutorials

• Yusuke Sugomori: Stochastic Gradient Descent for Denoising Autoencoders, http://yusugomori.com/docs/SGD_DA.pdf

• More detailed Java implementations are introduced in my book, Java Deep Learning Essentials.

  The book is available from Packt Publishing or Amazon.

Bitcoin wallet address: 34kZarc2uBU6BMCouUp2iudvZtbmZMPqrA