Researchers at Osaka Metropolitan University developed a machine learning-powered fluid simulation model that slashes ...

Abstract: Graph neural networks (GNNs) are capable of modeling graph data using various types of nodes and edges, and thus can be widely used in the fields of recommender systems and bioinformatics.

MLCommons announced new results for its MLPerf Inference v5.0 benchmark suite, which delivers machine learning (ML) system ...

The improved benchmarks will help enterprises select hardware for AI workloads, but are still no substitute for measuring ...

Bitcoin recently dropped from its all-time high of $109K to around $77K, sparking panic among short-term holders. But ...

The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...

Discover how BSidesSD 2025 challenged traditional GRC, spotlighted data poisoning, and promoted human-driven security insights. Read our highlights from this community event.

A modest sum has been turned into a big payout, catching the attention of the most experienced investors. Major holders of ...

About Tigera Tigera provides Calico, a unified network security and observability platform to prevent, detect and mitigate security breaches in Kubernetes clusters. Tigera's open-source offering, ...

Abstract: Scene Graph Generation (SGG) plays a vital role in determining the graph structure of an image by classifying objects based on their pairwise visual relationships. In the SGG, visually ...