Explore >> Select a destination
|
You are here 
|
distill.pub | ||
| | | | |
christopher-beckham.github.io
|
|
| | | | | Vicinal distributions as a statistical view on data augmentation | |
| | | | |
jakevdp.github.io
|
|
| | | | | ||
| | | | |
iclr-blogposts.github.io
|
|
| | | | | This blog post explores the interplay between the Data Processing Inequality (DPI), a cornerstone concept in information theory, and Function-Space Variational Inference (FSVI) within the context of Bayesian deep learning. The DPI governs the transformation and flow of information through stochastic processes, and its unique connection to FSVI is employed to highlight FSVI's focus on Bayesian predictive posteriors over parameter space. The post examines various forms of the DPI, including the KL divergence based DPI, and provides intuitive examples and detailed proofs. It also explores the equality case of the DPI to gain a deeper understanding. The connection between DPI and FSVI is then established, showing how FSVI can measure a predictive divergence inde... | |
| | | | |
kyunghyuncho.me
|
|
| | | |||
