Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural ... with a multisection ...

Recurrent neural networks, or RNNs, are a style of neural network that involve data moving backward among layers. ... This video is a good breakdown of the architecture in plain English.

Recurrent Neural Networks. ... RNNs do this by introducing feedback loops into the network’s architecture, enabling them to use information from previous calculations in order to determine a new ...

Convergence Analysis of Recurrent Neural Networks, vol. 13, 2004, pp. 15–32. ... "If You've Trained One, You've Trained Them All: Inter-Architecture Similarity Increases With Robustness." ...

Here, we'll discuss four major subtypes of software neural networks: convolutional, recurrent, generative adversarial, and spiking neural nets. We'll also take a look at Intel's hardware neural ...

Choosing what stimulus to focus on, a.k.a. attention, is also the main mechanism behind another neural network architecture, the transformer, which has become the heart of large language models ...

More information: Omid G. Sani et al, Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks, Nature Neuroscience (2024). DOI: 10.1038 ...