Therefore, we propose a multi-domain graph meta learning network (MDGML) to enable knowledge transfer and enhance information utilization through domain generalization and graph-based meta learning.

We further define autocorrelation and cross-correlation functions of signals on the graph, enabling us to obtain the solution to the optimal filtering on graphs, i.e., the corresponding Wiener ...

(Bloomberg) -- Alphabet Inc. shares gained after the company said it will offer “AI mode” in search to all US users, showing its commitment to redesigning its core business to keep pace with new rival ...

Download the CBSE Class 11 Maths Syllabus 2025-26 PDF for free. Check the updated course structure, topics, and marking ...

Quickly screen large amounts of possible materials for specific properties and select promising candidates for deeper ...

Insulet, (NASDAQ:PODD) listed under Nasdaq and included in the Nasdaq Index Funds, functions in the healthcare technology ...

The yeast nuclear endonuclease Rnt1 has a well-characterized role in the maturation of many ncRNA precursors. However, the scope and consequence of its function in mRNA degradation pathways is much ...

Alpha7x, the AI-Agent Data and Document Orchestration Engine built for mortgage operations, announced today that the United ...

The growing influence of AI agents in enterprise analytics signals a new era. These systems already produce meaningful, ...

Complex traits are influenced by genes and the environment, but especially the latter is difficult to pin down. This important study uses C. elegans to demonstrate that non-genetic differences in gene ...