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

An evnet driven model that uses financial time series data with New York Times information to form a LSTM recurrent neural network. There are 3 models. The first 2 models are based on price and volume ...
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 ...
C&EN

Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials

Department of Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States Department of Chemistry, Carnegie Mellon University, 5000 ...
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 ...
IEEE

Underwater Sound Speed Prediction by Mamba Neural Networks

Abstract: The underwater sound speed profile (SSP), that describing the distribution of sound speed, is an important parameter of underwater communication positioning, navigation and timing system due ...