Kapak Resmi

Deep Generative Modeling

This first comprehensive book on models behind Generative AI has been thoroughly revised to cover all major classes of deep generative models: mixture models, Probabilistic Circuits, Autoregressive Models, Flow-based Models, Latent Variable Models, GANs, Hybrid Models, Score-based Generative Models,...

Ful tanımlama

Kaydedildi:
Detaylı Bibliyografya
Yazar: Tomczak, Jakub M. (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: Elektronik Ekitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2024.
Edisyon:2nd ed. 2024.
Konular:
Artificial intelligence.
Machine learning.
Computer science > Mathematics.
Mathematical statistics.
Computer simulation.
Artificial Intelligence.
Machine Learning.
Probability and Statistics in Computer Science.
Computer Modelling.
Online Erişim:https://doi.org/10.1007/978-3-031-64087-2
Etiketler: Etiketle
Etiket eklenmemiş, İlk siz ekleyin!
İçindekiler:
  • Chapter 1 Why Deep Generative Modeling?
  • Chapter 2 Probabilistic modeling: From Mixture Models to Probabilistic Circuits
  • Chapter 3 Autoregressive Models
  • Chapter 4 Flow-based Models
  • Chapter 5 Latent Variable Models
  • Chapter 6 Hybrid Modeling
  • Chapter 7 Energy-based Models
  • Chapter 8 Generative Adversarial Networks
  • Chapter 9 Score-based Generative Models
  • Chapter 10 Deep Generative Modeling for Neural Compression
  • Chapter 11 From Large Language Models to Generative AI.

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