GitHub

HCLSM: Hierarchical Causal Latent State Machines

Current world models predict the future as a flat vector. They cannot tell you which object moved, why it moved, or what would happen if you pushed it differently. HCLSM changes this. The architecture ...
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 ...
Scientific Research Publishing

An In-Depth Analysis of Graph Neural Networks and Machine Learning Approaches for Drug Repositioning ()

1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...
IEEE

GNN-based Auto-Encoder for Short Linear Block Codes: A DRL Approach

Abstract: This paper presents a novel auto-encoder based end-to-end channel encoding and decoding. It integrates deep reinforcement learning (DRL) and graph neural networks (GNN) in code design by ...
News Medical

TxGNN improves drug repurposing by predicting treatments for rare diseases with no approved therapies

A recent study published in the journal Nature Medicine developed TxGNN, a graph-based foundation model for zero-shot drug repurposing. Only 5% to 7% of rare diseases have approved drugs. Expanding ...
Frontiers

A graph-based machine learning framework identifies critical properties of FVIII that lead to hemophilia A

Introduction: Blood coagulation is an essential process to cease bleeding in humans and other species. This mechanism is characterized by a molecular cascade of more than a dozen components activated ...
Frontiers

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics

Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering. An important ...