Codes associated to the thesis "Deep Learning and Radiative Heat Transfer" by Juan José García Esteban.
There are 8 notebook files, each one relating to diffeent computational methods and topics related to the thesis content:
- Simple_network.ipynb: Code related to the simple working example of section 1.3.
- Simple_hyperparameters: Code related to the description and effect of different sets of hyperparameters, corresponding to section 1.4.
- Interpolation_vs_Extrapolation.ipynb: Code related to the diffeence between interpolation and extrapolation regimes, corresponding to section 1.5.
- Deep_Reinforcement_Learning.ipynb: Code related to the use of different Deep Reinforcement Learning algorithms, corresponding to chapter 2.
- Scattering_Matrix.ipynb: Code related to the application of the scattering matrix formalism, corresponding to subsections 3.3.1 to 3.3.3.
- Mie_Theory.ipynb: Code related to the application of the Mie theory algorithm, corresponding to subsection 3.3.4.
- TDDA.ipynb: Code related to the application of the TDDA algorithm, corresponding to subsection 3.3.5.
- Appendix_A.ipynb: Code related to the simple networks explained in appendix A.
Additionally, there are two folders included in the repository:
- Datasets: includes datasets and material cosntants loaded by the notebooks, so they are necessary for many codes.
- SCUFF-EM: files used for the SCUFF-EM example of the sphere in appendix B.