Many existing methods for exploring the link between neural activity ... with a multisection neural network architecture and training approach." The researchers trained their RNN-based model using a ...

The biggest opportunities don’t come from people searching for your name. They come when someone’s searching for a solution—and the algorithm decides to introduce you.

This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using ...

They are variations of linear regression (and therefore not very powerful) and are extremely difficult to train because they require linear programming (and therefore very complex). However, a ...

Hyperparameter tuning is crucial for enhancing the accuracy and reliability of artificial neural networks (ANNs). This study presents an optimization of the Levenberg–Marquardt backpropagation neural ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the ...

Liquid neural networks can spur new innovations in AI and are particularly exciting in areas where traditional deep learning models struggle.