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 blog.fastforwardlabs.com
Under the Hood of the Variational Autoencoder (in Prose and Code)
| | jxmo.io
Introduction to variational autoencoders - Jack Morris
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| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | kyunghyuncho.me
Amortized Mixture of Gaussians (AMoG): A Proof of Concept for "Learning to X", or how I re-discovered simulation-based inference - Kyunghyun Cho
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| | www.depthfirstlearning.com
Variational Inference with Normalizing Flows ยท Depth First Learning
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| | [AI summary] The user has provided a detailed and complex set of questions and reading materials related to normalizing flows, variational inference, and generative models. The content covers topics such as the use of normalizing flows to enhance variational posteriors, the inference gap, and the implementation of models like NICE and RealNVP. The user is likely seeking guidance on how to approach these questions, possibly for academic or research purposes.
| | distill.pub
Exploring Bayesian Optimization
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| How to tune hyperparameters for your machine learning model using Bayesian optimization.