COMP9444 Neural Networks and Deep Learning - Week 9a Autoencoders PDF
Document Details
Uploaded by ChampionCognition5977
UNSW Sydney
2024
Alan Blair
Tags
Related
- Convolutional Neural Networks Handout PDF
- Deep Learning: Basics and Convolutional Neural Networks (CNN) PDF
- Artificial Intelligence for Big Data, Neural Networks, and Deep Learning PDF
- Artificial Intelligence for Big Data, Neural Networks & Deep Learning PDF
- Deep Neural Networks I PDF
- Representation Learning PDF
Summary
This document contains lecture notes on neural networks and deep learning, specifically focusing on autoencoders. The document covers topics such as autoencoder networks, regularized autoencoders, stochastic encoders, generative models, and variational autoencoders, along with Hopfield network and Boltzmann machine concepts.
Full Transcript
COMP9444: Neural Networks and Deep Learning Week 9a. Autoencoders Alan Blair School of Computer Science and Engineering November 4, 2024 Outline ➛ Autoencoder Networks ➛ Regularized Autoencoders ➛ Stochastic Encoders and Dec...
COMP9444: Neural Networks and Deep Learning Week 9a. Autoencoders Alan Blair School of Computer Science and Engineering November 4, 2024 Outline ➛ Autoencoder Networks ➛ Regularized Autoencoders ➛ Stochastic Encoders and Decoders ➛ Generative Models ➛ Variational Autoencoders 2 Hopfield Network and Boltzmann Machine X X E(x) = −( xi wij xj + bi x i ) i