Guided Sampling

Guided sampling enhances the generation process of various models by incorporating external information to direct the sampling towards desired outcomes. Current research focuses on improving efficiency and quality through techniques like integrating physics-based forces (e.g., in antibody design), leveraging geometric constraints (e.g., in visual localization), and employing advanced algorithms such as Restricted Boltzmann Machines and diffusion models with optimized solvers (e.g., for faster image generation). These advancements are impacting diverse fields, from accelerating quantum chemistry calculations and improving 3D object detection to enabling more controllable music generation and enhancing the design of biomolecules.