graph neural networks

Rule anchored graph learning improves synthetic identity fraud detection through multi relation structure rather than score level fusion

Synthetic Identity Fraud (SIF), in which fraudsters combine real and fabricated information to create untraceable identities, is a fast-growing and costly problem in payment systems. Prior work treats graph neural networks as an assumed improvement over transparent rule-based identity-linkage scoring, but rarely tests...

Interpretable Multimodal Engagement Prediction with Graph-based Mixture-of-Experts

Automatic engagement prediction is a significant aspect of Human-Computer Interaction (HCI) and affective computing, enabling systems to capture user interest and deliver timely interventions. In dyadic conversations, a person’s (target’s) engagement can be influenced by both their own behavioral signals and those of t...

Community detection via graph attention auto-encoders and decoders with non-negative matrix factorization

Edge-Adaptive Dynamic Spatiotemporal Graph Learning for Efficient Mobile Traffic Prediction in AIoT Cellular Networks

AIモデルの蒸留・盗用問題と量子実用化(Q-day)による知的所有権の再構築に関する総合調査報告 (英語副題: Comprehensive Investigation on AI Model Distillation, IP Theft, and Post-Q-Day Intellectual Property Restructuring)

日本語概要 (Japanese Abstract) 本調査報告書は、2025年末から2026年にかけて激化した最先端AIフロンティアモデルに対する「産業規模の敵対的蒸留攻撃(Adversarial Distillation Attacks)」の実態を網羅的に分析し、目前に迫る量子コンピューティングの実用化(Q-day)がAIの知的所有権(IP)、モデルの透明性、および産業構造に与える不可逆的な地...

Adaptive Graph Sparsification for Efficient Graph Neural Networks

This preprint presents an experimental study of graph sparsification for graph neural networks. The study evaluates multiple edge-selection strategies, including random, degree-based, structural, feature-based, and multi-criteria sparsification, across the Cora, CiteSeer, PubMed, Chameleon, and Squirrel datasets. The e...

AIモデルの蒸留・盗用問題と量子実用化(Q-day)による知的所有権の再構築に関する総合調査報告 (英語副題: Comprehensive Investigation on AI Model Distillation, IP Theft, and Post-Q-Day Intellectual Property Restructuring)

日本語概要 (Japanese Abstract) 本調査報告書は、2025年末から2026年にかけて激化した最先端AIフロンティアモデルに対する「産業規模の敵対的蒸留攻撃(Adversarial Distillation Attacks)」の実態を網羅的に分析し、目前に迫る量子コンピューティングの実用化(Q-day)がAIの知的所有権(IP)、モデルの透明性、および産業構造に与える不可逆的な地...

River ST-GNN Forecast: code and trained weights for river-stage forecasting in Ascension Parish, Louisiana

River ST-GNN Forecast provides research code and trained weights for the manuscript "An operational river-stage forecasting system using spatiotemporal graph neural network (ST-GNN) in Ascension Parish, Louisiana", prepared for submission to Hydrology and Earth System Sciences (HESS). The software compares a spatiotemp...

Dataset for "An operational river-stage forecasting system using spatiotemporal graph neural network (ST-GNN) in Ascension Parish, Louisiana"

This dataset accompanies the manuscript "An operational river-stage forecasting system using spatiotemporal graph neural network (ST-GNN) in Ascension Parish, Louisiana", prepared for submission to Hydrology and Earth System Sciences (HESS). It provides the evaluation data for a 68-gauge forecasting network comprising...

The Council That Never Forgets: Resolving the Stability-Plasticity Dilemma via Topological Prime Anchoring and Continual Multi-Agent Deliberation

Full Summary: The Council That Never Forgets Title: The Council That Never Forgets: Resolving the Stability-Plasticity Dilemma via Topological Prime Anchoring and Continual Multi-Agent Deliberation Author: Frank Morales Aguilera, Sovereign Machine Laboratory (SOMALA), Montreal, Quebec, Canada Date: October 1, 2026 Stat...

Microstate-Guided Dynamic Graph Neural Network with Prototypical Contrastive Learning for EEG Emotion Recognition

The Council That Never Forgets: Resolving the Stability-Plasticity Dilemma via Topological Prime Anchoring and Continual Multi-Agent Deliberation

Full Summary: The Council That Never Forgets Title: The Council That Never Forgets: Resolving the Stability-Plasticity Dilemma via Topological Prime Anchoring and Continual Multi-Agent Deliberation Author: Frank Morales Aguilera, Sovereign Machine Laboratory (SOMALA), Montreal, Quebec, Canada Date: October 1, 2026 Stat...