Data Products and the Semantic Backbone for AI Agents

When data is productized and semantics encoded, you unlock agentic AI at scale. Instead of assistants, you get executors: ...
Microsoft

Knowledge‐Guided Machine Learning for Operational Flood Forecasting

We present a knowledge‐guided machine learning framework for operational hydrologic forecasting at the catchment scale. Our approach, a Factorized Hierarchical Neural Network (FHNN), has two main ...
IEEE

Cost-Efficient Federated Learning in Massive IoT: A Physics-Inspired Graph Learning Approach

Abstract: Federated learning emerges as a key enabler toward pervasive intelligence across IoT ecosystems with provable privacy guarantees. While recent efforts on client selection have been made for ...
IEEE

Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning

Modern vehicles rely on a myriad of electronic control units (ECUs) interconnected via controller area networks (CANs) for critical operations. Despite their ubiquitous use and reliability, CANs are ...
i-SCOOP

Context graph

Discover what context graphs are, why they're revolutionizing AI systems, and who's building this trillion-dollar technology ...