Abstract: Markov Chain Monte Carlo (MCMC) is a method for drawing samples from non-standard probability distributions. Hamiltonian Monte Carlo (HMC) is a popular variant of MCMC that uses gradient ...
Supports most practical Explicit Runge-Kutta (ERK) methods. Tested on SD1.5, SDXL, and SD3. Decrease it to set more strict tolerances (better results) in exchange for slower inference times. Increase ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback