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When the 2012 Tesla Model S forced the industry to pay attention

The 2012 Tesla Model S did not just join the luxury sedan market, it rewrote the expectations for what an electric car could ...
IEEE

Mixed-Modality Clustering via Generative Graph Structure Matching

Abstract: The goal of mixed-modality clustering, which differs from typical multi-modality/view clustering, is to divide samples derived from various modalities into several clusters. This task has to ...
EurekAlert!

From 'one disease, one model' to 'one body, many diseases': TCM leads a new paradigm

Multimorbidity—when several chronic diseases occur at the same time—has become a growing barrier to effective healthcare.
Quanta Magazine

Distinct AI Models Seem To Converge On How They Encode Reality

Is the inside of a vision model at all like a language model? Researchers argue that as the models grow more powerful, they ...

Here's What Applied Digital Is Really Trying To Do With ChronoScale

Applied Digital (APLD) is restructuring by spinning out its cloud segment, ChronoScale, retaining 97% ownership, and ...

Astronomers Spot A Giant Cosmic Furnace So Hot It Defies Every Model We Have

A team of astronomers has uncovered an unusually hot 12 billion year-old gas cluster that challenges everything we thought we ...
Heart

Predicting 30-day mortality after hospital admission for heart failure: the National Heart Failure Audit for England and Wales

Background The National Heart Failure Audit gathers data on patients coded at discharge (or death) as having heart failure as ...
WUKY

Brain organoids are helping researchers, but their use also creates unease

Pea-size clusters of human cells called brain organoids inspire both hope and fear. Experts are debating how scientists can ...
GitHub

Sparse Surrogate Modeling for Combustion Chemistry via Time-Lag Autoencoders and Gradient-Based Clustering.

Schematic of the proposed methodology for surrogate modeling of chemical kinetics using Time-Lag Autoencoders' dimensionality reduction, and Gradient-Based Clustering. This methodology provides ...
IEEE

Unsupervised Deep Embedding for Fuzzy Clustering

Abstract: Deep fuzzy clustering employs neural networks to discover the low-dimensional embedding space of data, providing an effective solution to the clustering problem posed by high-dimensional ...