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 ...

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

The final, formatted version of the article will be published soon. Background Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among ...

Abstract: The increasing demand for robust security solutions across various industries has made Video Anomaly Detection (VAD) a critical task in applications such as intelligent surveillance, ...

Official implementation of our CleanPose, the first solution to mitigate the confoundering effect in category-level pose estimation via causal learning and knowledge distillation. You can generate the ...

Chinese and Singaporean researchers have developed a defense mechanism that poisons proprietary knowledge graph data, making ...

For hackers, the stolen data would be useless, but authorized users would have a secret key that filters out the fake ...

A decorated UVA engineer collects early-career honors for his leadership and contributions to the data mining field.

A simple way to give LLMs persistent memory across conversations. This server lets Claude or vscode remember information about you, your projects, and your preferences using a knowledge graph.

Abstract: Knowledge transfer among multiple networks, using predicted probabilities or intermediate-layer activations, has evolved significantly through extensive manual design, ranging from simple ...