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Backpropagation from Scratch in Python – Step by Step Neural Network Tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
GitHub

Graph Neural Network for Heat Transfer Problem

[1] F. Scarselli, M. Gori, A.C. Tsoi, M. Hagenbuchner, and G. Monfardini. The graph neural network model. IEEE Transactions on Neural Networks, 20(1):61 80, 2009.
Futurism

There’s Something Very Weird About This $30 Billion AI Startup by a Man Who Said Neural Networks May Already Be Conscious

Three years ago, OpenAI cofounder and former chief scientist Ilya Sutskever raised eyebrows when he declared that the era’s most advanced neural networks might have already become “slightly conscious.
IEEE

Parametric Activation Functions for Neural Networks: A Tutorial Survey

Abstract: Activation functions are pivotal in neural networks, determining the output of each neuron. Traditionally, functions like sigmoid and ReLU have been static and deterministic. However, the ...
Ars Technica

Here’s what’s really going on inside an LLM’s neural network

With most computer programs—even complex ones—you can meticulously trace through the code and memory usage to figure out why that program generates any specific behavior or output. That’s generally ...
marktechpost

This AI Paper Explores the Brain’s Blueprint via Deep Learning: Advancing Neural Networks with Insights from Neuroscience and snnTorch Python Libary Tutorials

The intersection of neuroscience and artificial intelligence has seen remarkable progress, notably through the development of an open-source Python library known as “snnTorch.” This innovative code, ...