This article presents a narrative review of Graph Neural Networks for Relational Data in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an interpretive...
Zen Revista, 10 IA· Zenodo (CERN European Organi...· 0 citations
This survey reviews deep learning architectures for transaction and financial fraud detection published strictly after 2024, using the Multi-task CNN Behavioural Embedding Model (MTCNN) proposed by Qu et al.[1] in 2024 as a conceptual anchor rather than as one of the post-2024 studies under review. MTCNN's core ideas —...
Dr. S. Jeyalaksshmi2 Ms. S. Jayanthi1*· World Journal of Pharmacy an...· 0 citations
This survey reviews deep learning architectures for transaction and financial fraud detection published strictly after 2024, using the Multi-task CNN Behavioural Embedding Model (MTCNN) proposed by Qu et al.[1] in 2024 as a conceptual anchor rather than as one of the post-2024 studies under review. MTCNN's core ideas —...
Dr. S. Jeyalaksshmi2 Ms. S. Jayanthi1*· World Journal of Pharmacy an...· 0 citations
This article presents a narrative review of Graph Neural Networks for Relational Data in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an interpretive...
Zen Revista, 10 IA· Zenodo (CERN European Organi...· 0 citations
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AdaH-Chain, a deterministic capacity-aware sharding framework that replaces unsafe floating-point operations with a symmetric fixed-point quantization mechanism to mathematically guarantee bit-wise consensus safety, is proposed and a Capacity-Aware GNN Sharding algorithm is introduced.
Zi-Yao Wang, Yong-Jiao Sun, Heng-Tai Zhao et al.· Tsinghua Science and Technol...· 0 citations
We propose that consciousness is a phase transition of a non-equilibrium dissipative structure, characterised by two independently controlled channels that must both be driven past threshold. The central result is an exclusion criterion: a macroscopic dissipative structure cannot be conscious unless it satisfies three...
FatJack· Zenodo (CERN European Organi...· 0 citations
HyGRAIL, a cost-aware and evidence-grounded framework that combines heterogeneous GNN triage with LLM-based hypothesis review, is proposed, which retrieves node-level associations and multi-hop relational paths from the knowledge graph and converts this structured evidence into natural language through template-based o...
Yi-Han-Qiu-Dan Sun, Zhi-Han Zhu, Zhi-Yuan Jiang et al.· 0 citations
H3DNAS is presented, a hardware-aware model compression framework that operates directly on ONNX computational graphs without requiring original source code, architecture class definition, or gradient access during search during search, and is the first source-code-free compression pipeline for 3D point cloud models.
Anchit Mulye, R. Baghel, Sujay Kumar Ingle et al.· 0 citations
This work proposes a method for refining heuristic-obtained clusters by grounding the authors' clustering on contrastive embeddings yielded by graph neural networks, and releases a publicly available dataset of Bitcoin transaction graphs containing a substantial number of clusters.
Hugo Schnoering, Roman Bresson, M. Vazirgiannis· 0 citations
Quantum-Enhanced Graph Neural Networks (QEN) presents a novel approach to graph neural network (GNN) learning, leveraging the principles of quantum entanglement to enhance both the training process and the network's expressive capabilities. This research investigates a method for utilizing entanglement to accelerate tr...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Medical AI is moving beyond recognition towards clinical dialogue and longitudinal prediction. Yet a central question remains: how would a patient’s state change under intervention? Statistical models learn future observations, whereas mechanistic models describe selected processes. Neither provides a common framework...
This article presents a narrative review of Graph Neural Networks for Relational Data in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an interpretive...
Zen Revista, 10 IA· Zenodo (CERN European Organi...· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
MIT News · Artificial Intelligence· news.mit.eduJul 15, 2026
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
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.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
