Frontiers

Neural networks and foundation models: two strategies for EEG-to-fMRI prediction

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...
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 ...
SiliconANGLE

Anaconda raises $150M+ to speed up Python-based AI projects

Developer tooling provider Anaconda Inc. today announced that it has closed a Series C funding round worth more than $150 million. Insight Partners led the investment with participation from Mubadala ...
Frontiers

Deriving equivalent symbol-based decision models from feedforward neural networks

Artificial intelligence (AI) has emerged as a transformative force across industries, driven by advances in deep learning and natural language processing, and fueled by large-scale data and computing ...
IEEE

Feedforward Control for an Interventional X-Ray: A Parallel Physical Model and Neural Network Approach

Abstract: Hard-to-model, often nonlinear dynamics limit the tracking performance of physical-model-based feedforward control in medical interventional X-ray (IX) systems. In this article, these ...
Scientific Research Publishing

Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks with a Nonpolynomial Activation Function Can Approximate Any Function. Neural Networks ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...