Variational Autoencoder articles

4/1/2019 • EN

Mixture of Variational Autoencoders - a Fusion Between MoE and VAE

Explores an unsupervised approach combining Mixture of Experts (MoE) with Variational Autoencoders (VAE) for conditional data generation without labels.

Generative Models Mixture Of Experts Neural Networks Unsupervised Learning Variational Autoencoder

Yoel Zeldes

11/11/2018 • EN

Variational Autoencoders Explained in Detail

A detailed technical tutorial on implementing a Variational Autoencoder (VAE) with TensorFlow, including code and conditioning on digit types.

Deep Learning Mnist Neural Networks Tensorflow Variational Autoencoder

Yoel Zeldes

9/14/2018 • EN

Variational Autoencoders Explained

A technical explanation of Variational Autoencoders (VAEs), covering their theory, latent space, and how they generate new data.

Deep Learning Generative Models Machine Learning Probability Density Function Variational Autoencoder

Yoel Zeldes

8/12/2018 • EN

From Autoencoder to Beta-VAE

Explores the evolution from basic Autoencoders to Beta-VAE, covering their architecture, mathematical notation, and applications in dimensionality reduction.

Beta Vae Deep Learning Generative Models Neural Networks Variational Autoencoder

Lilian Weng

7/16/2018 • EN

Neural Networks gone wild! They can sample from discrete distributions now!

Explains the Gumbel-Softmax trick, a method for training neural networks that need to sample from discrete distributions, enabling gradient flow.

Gradient Estimation Monte Carlo Neural Networks Reparameterization Trick Variational Autoencoder

Yoel Zeldes

Variational Autoencoder Articles

Mixture of Variational Autoencoders - a Fusion Between MoE and VAE

Variational Autoencoders Explained in Detail

Variational Autoencoders Explained

From Autoencoder to Beta-VAE

Neural Networks gone wild! They can sample from discrete distributions now!

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