论文信息 - LEARNING NUMBERS FROM GRAPHS

LEARNING NUMBERS FROM GRAPHS

The recent developments of statistical learning focused mainly on vector machines, i.e. on machines that learn from examples described by a vector of features. There are many fields where structured data must be handled; therefore, it would be desirable to learn from examples described by graphs. The presentation describes graph machines, which learn real numbers from graphs. Applications in the field of Quantitative Structure-Activity Relations (QSAR), which aim at predicting properties of molecules from their (graph) structures, are described.

Gérard Dreyfus | Arthur F. Duprat | Aurélie Goulon

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