GitHub

A python package that includes many methods for decoding neural activity

The package contains a mixture of classic decoding methods and modern machine learning methods. For regression, we currently include: Wiener Filter, Wiener Cascade, Kalman Filter, Naive Bayes, Support ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python Tropical Storm ...
Hosted on MSN

Deep Neural Network from Scratch in Python – Fully Connected Feedforward Tutorial

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 ...
gc.cuny

Programming Neural Networks in Python: Part II

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...
Frontiers

Sparse connectivity enables efficient information processing in cortex-like artificial neural networks

Neurons in cortical networks are very sparsely connected; even neurons whose axons and dendrites overlap are highly unlikely to form a synaptic connection. What is the relevance of such sparse ...
IEEE

Targeted Discrepancy Attacks: Crafting Selective Adversarial Examples in Graph Neural Networks

Abstract: In this study, we present a novel approach to adversarial attacks for graph neural networks (GNNs), specifically addressing the unique challenges posed by graphical data. Unlike traditional ...
IEEE

Performance Juxtapose of Plant Leaf Disease Detection using Adaptive Deep Convolutional Recurrent Neural Network (ADCRNN) in MATLAB Versus Python

Abstract: Leaf diseases can cause several detriments in crops' overall yield and fertility. While analyzing the various diseases that affect plants is imperative, identifying the diseases using ...
Live Science

'It will be comparable with the industrial revolution': Two legendary AI scientists win Nobel Prize in physics for work on neural networks

It's quick and easy to access Live Science Plus, simply enter your email below. We'll send you a confirmation and sign you up for our daily newsletter, keeping you up to date with the latest science ...
Scientific Research Publishing

Ketkar, N. and Moolayil, J. (2021) Convolutional Neural Networks. In: Ketkar, N. and Moolayil, J., Eds., Deep Learning with Python, Apress, 197-242.

ABSTRACT: The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For ...
GitHub

Hands-On Graph Neural Networks Using Python

Hands-On Graph Neural Networks Using Python This is the code repository for Hands-On Graph Neural Networks Using Python, published by Packt. Practical techniques and architectures for building ...