Recently, neural network model-based control has received wide interests in kinematics control of manipulators. To enhance learning ability of neural network models, the autoencoder method is used as ...

An autoencoder consists of two main parts: an encoder, which compresses the input image into a latent space representation, and a decoder, which reconstructs the image from this compressed ...

To speed up the optimization process, we transform the corresponding problem into a lower-dimensional latent space learned by a variational autoencoder. This is trained on a total of 6839 different 2D ...

The Autoencoder.py file implements the Autoencoder class in torch. The training.py file performs the training over the entire training dataset. The testing.py file gets a random sample from the ...

Article citations More>>. Ng, A. (2011) Sparse Autoencoder. CS294A Lecture Notes, 72, 1-19. has been cited by the following article: TITLE: A Double-Weighted Deterministic Extreme Learning Machine ...