April 2025
Intermediate to advanced
456 pages
11h 35m
Portuguese (Portugal, Brazil)
Content preview from Generative Deep Learning, 2ª Edição
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Capítulo 3. Autoencodificadores Variacionais
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Em 2013, Diederik P. Kingma e Max Welling publicaram um artigo que lançou as bases para um tipo de rede neural conhecido como autoencoder variacional (VAE).1 Esta é agora uma das arquitecturas de aprendizagem profunda mais fundamentais e conhecidas para a modelação generativa e um excelente ponto de partida para a nossa viagem à aprendizagem profunda generativa.
Neste capítulo, começaremos por construir um autoencoder padrão e depois veremos como podemos alargar esta estrutura para desenvolver um autoencoder variacional. Ao longo do caminho, vamos analisar ambos os tipos de modelos, para compreender como funcionam ...
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