This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpropagation through ODE solutions is supported using the adjoint method for constant memory cost. For ...
The official code for the paper DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps (Neurips 2022 Oral) and DPM-Solver++: Fast Solver for Guided Sampling of ...
Previous high-order solvers are unstable for guided sampling: Samples use the pre-trained DPMs on ImageNet 256 256 with a classifier guidance scale 8.0, varying different samplers (and different ...
Abstract: When solving ordinary differential equations in C/C++ libraries, the ODE’s right-hand-side is hard-coded and compiled ahead of time. This kind of static binding technique make it hard for ...
Abstract: In this paper we consider the numerical solution of matrix Riccati equation with the different ODE solvers. A comparison of following extrapolation methods is undertaken: ...
I've spent the last few hours looking for an ODE solver that I can use for my course assignments. I basically need to be able to input the systems of equations and then, for different initial ...
Nowadays, text-to-image synthesis is gaining a lot of popularity. A diffusion probabilistic model is a class of latent variable models that have arisen to be state-of-the-art on this task. Different ...
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