Sentence examples for learning to generate from inspiring English sources

The madcap "Floof," a depiction of a computer learning to generate poetry, drawn from a story by Stanislaw Lem, is endearing.

We used a RW model of associative learning to generate predictors of learning-dependent changes in brain activity (as indexed by the BOLD signal) and inter-regional connectivity over time.

For instance, it provides insurers with preventive solutions, applying big behavioral data and machine learning to generate the best predictions on default, bad debt, prepayments and customer churn resulting in individualized risk assessment.

"It is one of the first visualisations to use machine learning to generate its content using the Google Natural Language API, which analyses text and extracts information about people, places, and events," Google News Lab Data editor Simon Rogers writes in the announcement.

Zhao and Murphy 12 instead uses machine learning to generate the shape of the nucleus and the cytoplasm as well as the texture of the nucleus.

The top-down process concerns promoting students' self-directed learning to generate more questions, reach for the answers and discover the answers through a process of systematic inquiry as well as maintaining important professional standards.

So the more we click or search or generally Internet in sexist, racist ways, the algorithms learn to generate those results and ads (supposedly the results we would expect to see).

The orchestra showed in the Götterdämmerung excerpts how it has learned to generate the glowing, intense sound that is so characteristic of Barenboim's Wagner, the Rhine Journey joyous, expansive, the Funeral March fierce and unremitting.

i fed a recurrent neural network with the scripts for every episode of friends and it learned to generate new scenes pic.twitter.com/RIPvYuzEJM When asked what he may attempt next, Herd responded: "Maybe Frasier or Seinfeld.

The pre-trained convolutional networks have already learnt to generate rich image representations that have proven adequate for image classification and segmentation.

Using relatively simple grammar rules, we learn to generate schemes that satisfy a set of requirements stated in a design guideline.