The application of diffusion models in 3D LiDAR scene completion is limited due to diffusion's slow sampling speed. Score distillation accelerates diffusion sampling but with performance degradation, ...

The MOD consists of an Online Tokenizer and a Dense Predictor, which employs self-distillation and self-modeling on masked patches, promoting swift convergence and efficient representation learning. .

Distillation is one of the most common and important separation processes in chemical engineering. It can be used to purify, fractionate, or recover valuable components from a mixture of liquids ...

Simultaneous design and control of catalytic distillation columns using comprehensive rigorous dynamic models. Industrial & Engineering Chemistry Research, 57, 2587–2608. American Chemical Society.

🚀 PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" - kristofe/3D_diffusion_distiller. Skip to content. Navigation Menu Toggle navigation. Sign ...

Distillation is a process of extracting knowledge from a larger AI model to create a smaller one. It can allow a small team with virtually no resources to make an advanced model.