Deep learning reveals how auditory cortex neurons split up natural sound coding

Over the past decades, computer scientists have introduced numerous artificial intelligence (AI) systems designed to emulate the organization and functioning of networks of neurons in the brain.
IEEE

Autoencoder-Based Analog Fountain Codes for Short Packet Communications

Abstract: Short packet transmission is crucial for ultra-reliable and low-latency communications (URLLC), yet designing efficient channel codes for such scenarios remains challenging due to the ...
New Scientist

Quantum neural network may be able to cheat the uncertainty principle

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Hosted on MSN

Build a deep neural network from scratch in Python

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...
InfoWorld

PythoC: A new way to generate C code from Python

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...
IEEE

XAI Driven Software Defect Prediction Using Adaptive Feature Engineering Coupled With Autoencoder and Multi-Layer Perceptron: An Empirical Study

Abstract: Software defect prediction is essential for ensuring the reliability and robustness of software prototypes during development. The current study has proposed a novel strategy that integrates ...
GitHub

Source code for a neural network-based framework for signal separation in spatio-temporal gravity data

B. Heller-Kaikov, R. Pail and M. Werner, Neural network-based framework for signal separation in spatio-temporal gravity data. Computers and Geosciences (2025), doi ...
The Journal

Network to Code Intros AI Assistant for Enterprise Network Teams

Network automation firm Network to Code has introduced NautobotGPT, an AI-powered assistant aimed at helping enterprise network engineers create, test, and troubleshoot automation tasks more ...