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.

Add your perspective 2 Distillation column model To optimize a distillation column using process simulation, you need to create a realistic and accurate model of the column.

The significant improvements in point cloud representation learning have increased its applicability in many real-life applications, resulting in the need for lightweight, better-performing models.

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

Learn how to scale up a distillation column from lab to plant by considering feed data, column design, heat and mass balance, control system, safety, and economics.

🚀 PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" - kristofe/3D_diffusion_distiller ...

Abstract 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 ...

David Sacks says OpenAI has evidence that Chinese company DeepSeek used a technique called "distillation" to build a rival model.

How DeepSeek used distillation to train its artificial intelligence model, and what it means for companies such as OpenAI ...