Sure to be influential, Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, ...

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Hopfield and Hinton developed a theory for neural networks based on the idea of statistical mechanics ... and this algorithm ...

This course cannot be taken with ST102 Elementary Statistical Theory, ST107 Quantitative Methods (Statistics ... Please note that during 2021/22 academic year some variation to teaching and learning ...

Personally, I’m not particularly offended by cat-eating,” says Christopher Rufo. “I was a vegetarian most of my life, but ...

This research note is the first in a series exploring the emerging impact of causal AI. It will focus on the growing ...

Just as the PC and cloud defined much of Microsoft’s first 50 years, and just as its struggles in mobile set the company back ...

The 2024 Nobel Prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their fundamental discoveries in ...

Lattice field theory is still tricky ... corresponds to another statistical technique used in deep learning called generative ...

Statistical physics is a branch of physics that uses probability theory and statistics to solve ... behaviour of its components. A deep learning algorithm is presented to classify single-particle ...

Researchers show that for the first time they have achieved atomic-scale observations of grain rotation in polycrystalline materials. Using state-of-the-art microscopy tools, the scientists were able ...

This course cannot be taken with ST102 Elementary Statistical Theory, ST107 Quantitative Methods (Statistics ... Please note that during 2021/22 academic year some variation to teaching and learning ...