Small quantum system outperforms large classical networks in real-world forecasting

Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a ...
IEEE

Artificial Neural Network-Based Prediction of Total Project Cost of Residential Dwellings in Quezon City, Philippines Utilizing Engineering Building Parameters and Site ...

Abstract: This study develops an Artificial Neural Network (ANN)-based prediction model to estimate the total project cost (TPC) of residential dwellings in Quezon City, the largest local government ...
GitHub

Neural-Network-with-Financial-Time-Series-Data

This is an evnet driven model that uses stock price data together with the New York Times News to form a LSTM recurrent neural network. There are 3 models. The first 2 models are based on price and ...
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 ...
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 ...
PNAS

Unified protein–small molecule graph neural networks for binding site prediction

Accurately identifying small molecule binding sites on proteins is fundamental to understanding protein function and enabling structure-based drug discovery, yet this critical step remains a major ...
Frontiers

Prediction of mechanical properties of steel fibre-reinforced concrete under elevated temperature using artificial neural network techniques (ann)

This study investigates the mechanical performance of Steel Fibre-Reinforced Concrete (SFRC) subjected to elevated temperatures using artificial neural network (ANN) modeling. While existing ...
C&EN

RTK_RAG: Leveraging Retrieval Augmented Generation with Multi-Window Convolutional Neural Networks for Superior ATP Binding Site Prediction in Receptor Tyrosine Kinases

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are ...
Phys.org

Self-learning neural network cracks iconic black holes

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...