Explore >> Select a destination

You are here

 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
| | tiao.io
A Tutorial on Variational Autoencoders with a Concise Keras Implementation | Louis Tiao
2.6 parsecs away

Travel
| | An in-depth practical guide to variational encoders from a probabilistic perspective.
| | jxmo.io
Introduction to variational autoencoders - Jack Morris
3.0 parsecs away

Travel
| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | www.depthfirstlearning.com
Variational Inference with Normalizing Flows ยท Depth First Learning
3.1 parsecs away

Travel
| | [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.
| | sander.ai
The geometry of diffusion guidance Sander Dieleman
6.8 parsecs away

Travel
| More thoughts on diffusion guidance, with a focus on its geometry in the input space.