The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Multi area RNN models fitted to in-vivo cortical activity predict behavioral changes induced by optogenetic perturbations, if biologically informed connectivity constraints on the optogenetically ...

The most powerful artificial intelligence tools all have one thing in common. Whether they are writing poetry or predicting ...

A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers at Sandia National Lab. Abstract “The finite element method (FEM) is one of ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...