Δ ℚuantitative √ourney

On Tensor Networks and Non-Linearity

Tensor Networks can be seen as a higher-order generalization of traditional deep neural networks, and yet they lack an explicit non-linearity such as applying the ReLU or sigmoid function as we do with neural nets. We explore how non-linearity arises in these Tensor Networks and demonstrate their utility on a simple learning task.