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 ...

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...

Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...

In the ever-evolving landscape of artificial intelligence, there is a growing interest in leveraging insights from neuroscience to create more ...

In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet, the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...