Feature extraction of neural networks applied to magnetic models
"The weight matrices of a neural network capable of classifying the phases of the square lattice Ising model, were studied in order to identified the physical features that such an algorithm identifies. A review of the theory of neural networks and condensed matter physics is also included.&quo...
- Autores:
-
Salazar Jaramillo, Santiago
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2018
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/39082
- Acceso en línea:
- http://hdl.handle.net/1992/39082
- Palabra clave:
- Modelo de Ising
Redes neurales (Computadores)
Mecánica estadística
Campos magnéticos
Física
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-sa/4.0/
| Summary: | "The weight matrices of a neural network capable of classifying the phases of the square lattice Ising model, were studied in order to identified the physical features that such an algorithm identifies. A review of the theory of neural networks and condensed matter physics is also included."--Tomado del Formato de Documento de Grado |
|---|