Abstract: In the realm of deep learning, the lack of transparency in complex models is a major obstacle for wider adoption and trust in artificial intelligence systems. Current explainability methods ...

It is exciting to see Ignite UI open-sourcing their Angular components. By making these enterprise-grade tools accessible to the broader community, Infragistics is lowering the ...

Could 2026 be the year of the beautiful back end? We explore the range of options for server-side JavaScript development, from Express to Next and all the rest. A grumpy Scrooge of a developer might ...

Model misspecification is a common challenge in population genetic inference, as oversimplified mathematical models often fail to capture complex evolutionary processes. Here, we introduce a framework ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...

Abstract: Knowledge graph completion (KGC) tasks aim to infer missing facts in a knowledge graph (KG) for many knowledgeintensive applications. However, existing embedding-based KGC approaches ...