This repository contains the implementation of a Physics-Informed Neural Network (PINN)-Enhanced Finite Difference Method (FDM) for modeling energy balance in hydraulic fracture propagation. The ...

Abstract: Channel estimation is crucial in wireless communications. However, in many papers neural networks are frequently tested by training and testing on one example channel or similar channels.

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

Summary: Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks. Unlike traditional methods that only cluster nodes, this approach groups ...

Abstract: Real-time visualization of neural network training in web applications presents distinct challenges. Existing desktop solutions burden the user's hardware, requiring powerful machines and ...

Introduction: Segmentation of echocardiograms plays a crucial role in clinical diagnosis. Beyond accuracy, a major challenge of video echocardiogram analysis is the temporal consistency of consecutive ...

Alongside text-based large language models (LLMs), including ChatGPT in industrial fields, GNN (Graph Neural Network)-based graph AI models that analyze unstructured data such as financial ...