Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...

(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...

Artificial neural networks are big business these days. If you’ve been on Twitter recently, or voted in the last election, chances are your data was processed by one. They are now being used in ...

The field of statistical mechanics applied to neural networks and Boltzmann machines has grown into a multidisciplinary research area that bridges the gap between theoretical physics, mathematics and ...