Unsupervised Learning

Tech Talk: Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference

Amazon Machine Learning Community Tech Talk, Berlin.

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Louis Tiao
Contributed Talk: Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference featured image

Contributed Talk: Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference

ICML 2018 Workshop on Theoretical Foundations and Applications of Deep Generative Models (TAGDM), Stockholm.

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Louis Tiao
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference featured image

Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference

We derive cycle-consistent adversarial learning (CycleGAN) as a special case of variational inference in a latent-variable model with implicit priors, establishing a Bayesian …

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Louis Tiao
A Tutorial on Variational Autoencoders with a Concise Keras Implementation featured image

A Tutorial on Variational Autoencoders with a Concise Keras Implementation

We give an in-depth practical guide to variational autoencoders from a probabilistic perspective.

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Louis Tiao