Image Generation with langevin dynamics
In the field of machine learning, Diffusion Probabilistic Models have emerged as a prominent category of generative models. Their main objective is to learn a diffusion process that describes the probability distribution of a given dataset. The essence of diffusion-based generative models finds its...
- Autores:
-
Almanza Márquez, David Leonardo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2024
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/74510
- Acceso en línea:
- https://hdl.handle.net/1992/74510
- Palabra clave:
- Diffusion probabilistic models
Machine learning
Statistical physics
Langevin equation
Synthetic data generation
Física
Ingeniería
- Rights
- openAccess
- License
- Attribution-NonCommercial 4.0 International