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Adversarial Latent Autoencoders
Introducing the Adversarial Latent Autoencoder (ALAE), a general architecture that can leverage recent improvements on GAN training procedures.
autoencoders generative-adversarial-networks latent-space disentanglement
A deep generative model for dimensionality reduction and clustering.
dimensionality-reduction clustering autoencoders variational-autoencoders
How to Detect Data-Copying in Generative Models
I propose some new definitions and test statistics for conceptualizing and measuring overfitting by generative models.
generative-modeling data-copying generative-adversarial-networks variational-autoencoders
Adversarial Latent Autoencoders
Harnessing the latent power of autoencoders, one disentanglement at a time.
autoencoders generative-adversarial-networks adversarial-latent-autoencoders tutorial
A Tutorial on VAEs: From Bayes' Rule to Lossless Compression
An overview of the VAE and a tour through various derivations and interpretations of the VAE objective.
variational-autoencoders autoencoders bayes-rule loseless-compression
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
We propose a simple framework (GraphEDM) and a comprehensive Taxonomy to review and unify several graph representation learning methods.
graph-neural-networks graph-convolutional-networks autoencoders graph-regularization
Training Deep AutoEncoders for Collaborative Filtering.
autoencoders recommendation-systems pytorch tutorial
Unsupervised Speech Decomposition
This demo webpage provides sound examples for SpeechSplit, an autoencoder that can decompose speech into content, timbre, rhythm and pitch.
speech autoencoders unsupervised-learning decomposition
A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
graph-embedding graph-convolution node-embedding node-classification
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