Hacker

The Beginner's Guide to Neural Networks

I’ve always been obsessed with the invisible forces shaping the future. Biases, on the other hand, act like a pre-set adjustment. Think of it as a worker starting with a partially assembled product ...
marktechpost

Using Graphify and NetworkX to Map Python Codebase Structure with God Nodes, Communities, and Architecture Visualizations

In this tutorial, we build a fully offline Graphify workflow that turns a realistic multi-module Python application into a knowledge graph. We start by installing Graphify and supporting graph ...
IEEE

A Generative Graph Augmentation Neural Network for Traffic Risk Prediction on Online Crowd Queries

Abstract: In the existing traffic prediction scenarios, the lack of accompanying event data, noise interference and insufficient supervised signals seriously restrict the effect of actual traffic ...
IEEE

A Text-Guided Graph Neural Network for Predicting Long-Range Trajectories of Sea-Surface Objects

Abstract: The sea-surface environment is influenced by various factors, such as wind, waves, tides, and ocean currents. Interactions among various factors, combined with heterogeneous spatiotemporal ...
GitHub

This repo describes python code and input data files for "Forecasting stock return distributions around the globe with quantile neural networks".

torch 2.2.2 PyTorch framework for neural networks. The documented GPU setup targets the official CUDA 12.1 wheel. FF3.CSV Ken French Data Library Full file included Fama-French 3-factor returns. Only ...