ProbDiff

This is a reimplimentation of the paper titled "Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Math

Forward Trajectory

we label data distribution $q(x^{(0)})$. the data distribution is gradualy converted into a well behaved (analytically tractable) distribution $\pi(y)$ by repeated application of a Marko diffusion kernel $T_{\pi}(y|y`;\beta) for \pi(y)$, where $\beta$ is the diffusion rate.