GitHub

Internet-scale Neural Networks

Welcome! Bittensor is an open source platform on which you can produce competitive digital commodities. These digital commodities can be machine intelligence, storage space, compute power, protein ...
IEEE

Contra Harmonic Mean Labeling of Some Graphs and Python-Based Continuous-Time Neural Networks for Solving the Travelling Salesman Problem in Artificial Intelligence

Abstract: In this paper, we prove Contra Harmonic Mean Labeling for some star related graphs such as $\mathrm{K}_{1, \mathrm{n}}, S(\mathrm{K}_{1, \mathrm{n ...
Hosted on MSN

Backpropagation from scratch in Python – step by step neural network tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
IEEE

A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges

Abstract: Dynamic Graph Neural Networks (GNNs) combine temporal information with GNNs to capture structural, temporal, and contextual relationships in dynamic graphs simultaneously, leading to ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
PNAS

Graph neural networks for predicting metal–ligand coordination of transition metal complexes

Transition metal complexes (TMCs) are of great scientific and practical interest for applications in catalysis, biological systems, photochemistry, and sustainability, with properties highly dependent ...