What can you do about data sparsity? What do you do when you have a matrix with a bunch of zeros in it, and you can't get a good look at a complex system because so many of the nodes are empty? Matrix ...

A machine-learning approach developed for sparse data reliably predicts fault slip in laboratory earthquakes and could be key to predicting fault slip and potentially earthquakes in the field. A ...

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...

AI is rapidly being adopted in the pharmaceutical industry, particularly for improving predictive models in drug discovery and early preclinical development. Fueled by the large amounts of data ...

An innovative approach to artificial intelligence (AI) enables reconstructing a broad field of data, such as overall ocean temperature, from a small number of field-deployable sensors using ...

One of the biggest miscalculations made around Covid-19 last year is we assumed that because it was a novel virus, we were starting from a place of zero data. This caused a number of problems. As ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

AI is rapidly being adopted in the pharmaceutical industry, particularly for improving predictive models in drug discovery and early preclinical development. Fueled by the large amounts of data ...