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graph neural networks

1,828 papers

#graph neural networks Book Open access Sep 2026

Autonomous AI-Based Cloud Security Monitoring and Attack Prediction System Using Deep Neural Networks

Autonomous AI-Based Cloud Security Monitoring and Attack Prediction System Using Deep Neural Networks presents a comprehensive approach to modern cloud cybersecurity by combining cloud monitoring, artificial intelligence, deep learning, anomaly detection, attack classification, threat prediction, risk assessment, and a...

Anantha Raman Rathinam, M. Sakthivel, Dr. J. Gladson Maria Britto · 0 citations
#graph neural networks Open access Sep 2026

FedTGNN-SS: leakage-controlled evaluation of federated semi-supervised graph neural networks for gestational and other diabetes prediction (code, protocol and results)

Code, prespecified analysis protocol, leakage unit tests and run-level results accompanying the article 'Federated Semi-Supervised Graph Neural Networks for the Prediction of Gestational and Other Diabetes from Tabular Records: A Leakage-Controlled Evaluation'. No patient data are included; the datasets are available f...

Gonzalo Daniel · 0 citations
#graph neural networks Open access Sep 2026

FedTGNN-SS: leakage-controlled evaluation of federated semi-supervised graph neural networks for gestational and other diabetes prediction (code, protocol and results)

Code, prespecified analysis protocol, leakage unit tests and run-level results accompanying the article 'Do Federated Semi-Supervised Graph Neural Networks Improve Tabular Clinical Prediction? A Leakage-Controlled Evaluation in Diabetes'. No patient data are included; the datasets are available from Kaggle and the UCI...

Gonzalo Daniel · 0 citations
#graph neural networks Open access Sep 2026

FedTGNN-SS: leakage-controlled evaluation of federated semi-supervised graph neural networks for gestational and other diabetes prediction (code, protocol and results)

Code, prespecified analysis protocol, leakage unit tests and run-level results accompanying the article 'Do Federated Semi-Supervised Graph Neural Networks Improve Tabular Clinical Prediction? A Leakage-Controlled Evaluation in Diabetes'. No patient data are included; the datasets are available from Kaggle and the UCI...

Gonzalo Daniel · 0 citations
#graph neural networks Open access Sep 2026

Artificial Intelligence in the Energy Sector: A Review of Common Applications

Artificial intelligence (AI) is increasingly being applied across the energy sector to support forecasting, diagnosis, optimization, control, and system planning. This review synthesizes common applications of AI in electricity-centered energy systems, including load and renewable-energy forecasting, electricity-market...

Bibek Ghimire · 0 citations
#graph neural networks Sep 2026

Multimodal Trilemma GNN‐LLM‐XAI Framework Resolving Accuracy Transparency Comprehensibility in E‐Commerce Fraud Detection

ABSTRACT E‐commerce platforms face an escalating challenge from sophisticated financial fraud and cyberattacks, yet current detection systems suffer from a fundamental trilemma: achieving high detection accuracy, providing expert‐level transparency, and ensuring user comprehensibility simultaneously. Graph neural netwo...

Altaf Hussain, Muhammad Imran Khalid, Razaz Waheeb Attar et al. · 0 citations
#graph neural networks Open access Sep 2026

Artificial Intelligence in the Energy Sector: A Review of Common Applications

Artificial intelligence (AI) is increasingly being applied across the energy sector to support forecasting, diagnosis, optimization, control, and system planning. This review synthesizes common applications of AI in electricity-centered energy systems, including load and renewable-energy forecasting, electricity-market...

Bibek Ghimire · 0 citations
#reinforcement learning Open access Sep 2026

Artificial Intelligence in CPU and ASIC Design: Applications, Design-Space Exploration, and Engineering Constraints

Modern CPU and application-specific integrated circuit (ASIC) development requires engineers to search large design spaces while satisfying power, performance, area, timing, and correctness constraints. Artificial intelligence (AI) is increasingly being integrated into electronic design automation (EDA) to accelerate p...

Jerome Bernard Auman · 0 citations
#reinforcement learning Open access Sep 2026

Performance and Hardware Complexity Analysis of Ripple-Carry and Carry-Lookahead Adders for Logic Synthesis Optimization

As integrated circuit fabrication approaches physical limits, classical Electronic Design Automation (EDA) algorithms struggle with high-dimensional search spaces during multi-objective Power, Performance, and Area (PPA) optimization. Binary addition circuits form the core bottleneck of arithmetic processing units; thu...

Enrico Jose Gonzaga · 0 citations
#reinforcement learning Open access Sep 2026

Machine Learning in Industrial Logic Gate Synthesis: Operational Capabilities and Verification Constraints

AbstractProgrammable Logic Controllers (PLCs) rely on fixed-threshold comparators that frequently trigger false emergency trips when exposed to electromagnetic interference, thermal drift, and mechanical vibrations. This paper evaluates applying machine learning to industrial logic gate synthesis, using Graph Neural Ne...

Nico Ivan Rosales · 0 citations
#graph neural networks Open access Sep 2026

FedTGNN-SS: leakage-controlled evaluation of federated semi-supervised graph neural networks for gestational and other diabetes prediction (code, protocol and results)

Code, prespecified analysis protocol, leakage unit tests and run-level results accompanying the article 'Federated Semi-Supervised Graph Neural Networks for the Prediction of Gestational and Other Diabetes from Tabular Records: A Leakage-Controlled Evaluation'. No patient data are included; the datasets are available f...

Gonzalo Daniel · 0 citations
#graph neural networks Open access Sep 2026

Artificial Intelligence in the Energy Sector: A Review of Common Applications

Artificial intelligence (AI) is increasingly being applied across the energy sector to support forecasting, diagnosis, optimization, control, and system planning. This review synthesizes common applications of AI in electricity-centered energy systems, including load and renewable-energy forecasting, electricity-market...

Bibek Ghimire · 0 citations

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Microsoft Research Blog Jul 13, 2026

Verifying Rust cryptography in SymCrypt, from standards to code

Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.

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