Książka Exploring Deep Learning Architectures for Graph Applications Irwin King

Exploring Deep Learning Architectures for Graph Applications

Autor: Irwin King
Język: Angielski
Oprawa: Miękka
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
226.83
Graph-structured data are the backbone of numerous real-world machine learning tasks, such as social...

Informacje o książce

Autor
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2020
strony
136
EAN
9786202917650
ISBN
6202917652
Enbook ID
36917993
Waga
221
Wymiary
150 x 220 x 8

Pełny opis

Graph-structured data are the backbone of numerous real-world machine learning tasks, such as social networks, recommender systems, traffic networks, and so on. The fundamental challenge in solving these tasks is to find a way to encode graph structures as well as to incorporate various node or edge information so that machine learning models can easily exploit them. In this dissertation, we explore deep learning architectures, especially the graph neural networks for multiple graph learning applications, i.e., node classification, link prediction, spatiotemporal graph forecasting on irregular grid, and supervised sequence learning problems.

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