eLife

Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.
Deep Learning with Yacine on MSN

Deep neural network from scratch in Python – fully connected feedforward tutorial

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
IEEE

V-DCRNN: Virtual Network-Based Diffusion Convolutional Recurrent Neural Network for Estimating Unobserved Traffic Data

Abstract: Several studies have analyzed traffic patterns using Vehicle Detector (VD) and Global Positioning System (GPS) data. VD records the speed of vehicles passing through detectors, GPS data ...
IEEE

Adaptive Output Feedback Control Using Lyapunov-Based Deep Recurrent Neural Networks (Lb-DRNNs)

Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...