Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural ...

Abstract: This paper presents an analog RF-domain implementation of a Vanilla Recurrent Neural Network (RNN) for real-time anomaly detection in 5G and beyond wireless networks. Real-time analysis is ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

This repository contains the official implementation for the paper "Evolving Spatially Embedded Recurrent Spiking Neural Networks for Control Tasks." The code implements a framework for evolving ...

Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...

1 School of Mechanical Engineering, Vellore Institute of Technology, Chennai, India 2 Centre for e-Automation Technologies, Vellore Institute of Technology, Chennai, India Introduction: Friction Stir ...

Step-by-step coding a full deep neural network with zero libraries — just logic and Python. #NeuralNetwork #PythonCode #DeepLearning Trump announces two new national holidays, including one on ...

Welcome to Learn with Jay – your go-to channel for mastering new skills and boosting your knowledge! Whether it’s personal development, professional growth, or practical tips, Jay’s got you covered.