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A basic example of this is quantum state tomography, where a quantum state is learned from measurement. [1] Other examples include learning Hamiltonians, [2] [3] learning quantum phase transitions, [4] [5] and automatically generating new quantum experiments.
Applications of machine learning (ML) in earth sciences include geological mapping, gas leakage detection and geological feature identification.Machine learning is a subdiscipline of artificial intelligence aimed at developing programs that are able to classify, cluster, identify, and analyze vast and complex data sets without the need for explicit programming to do so. [1]
Libratus, a poker AI that beat world-class poker players in 2017, intended to be generalisable to other applications. [ 25 ] The Matchbox Educable Noughts and Crosses Engine (sometimes called the Machine Educable Noughts and Crosses Engine or MENACE) was a mechanical computer made from 304 matchboxes designed and built by artificial ...
Features retinopathy grade and risk of macular edema 1200 Images, Text Classification, Segmentation 2008 [278] [279] Messidor Project Liver Disorders Dataset Data for people with liver disorders. Seven biological features given for each patient. 345 Text Classification 1990 [280] [281] Bupa Medical Research Ltd. Thyroid Disease Dataset
For example, there is a prototype, photonic, quantum memristive device for neuromorphic (quantum-)computers (NC)/artificial neural networks and NC-using quantum materials with some variety of potential neuromorphic computing-related applications, [367] [368] and quantum machine learning is a field with some variety of applications under ...
Deep learning applications have been used for regulatory genomics and cellular imaging. [33] Other applications include medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. [34] Deep learning has been applied to regulatory genomics, variant calling and pathogenicity scores. [35]