GitHub - gully/bombcat: Examples of how to fit models to data with Gaussian Process regression

bombcat

Basically, these are just cool stats examples. Info here:

and

Jan. 6, 2015 update I converted my old hack of Dan Foreman-Mackey's Gaussian Process tutorial into an IPython Notebook.

Name		Name	Last commit message	Last commit date
gpu_performance_LS		gpu_performance_LS
.gitignore		.gitignore
DFM_GP_example.py		DFM_GP_example.py
LICENSE		LICENSE
README.md		README.md
bombcat-SiGaps-data.ipynb		bombcat-SiGaps-data.ipynb
bombcat-SiGaps-emcee.ipynb		bombcat-SiGaps-emcee.ipynb
bombcat-SiGaps-opt.ipynb		bombcat-SiGaps-opt.ipynb
bombcat-pytorch-emcee.ipynb		bombcat-pytorch-emcee.ipynb
bombcat-pytorch.ipynb		bombcat-pytorch.ipynb
bombcat.ipynb		bombcat.ipynb
etalon.py		etalon.py
faster_more_accurate_science.ipynb		faster_more_accurate_science.ipynb
gpu_performance_LS.csv		gpu_performance_LS.csv
least_squares_covariance.png		least_squares_covariance.png
least_squares_cpu.py		least_squares_cpu.py
least_squares_cpu_update.py		least_squares_cpu_update.py
least_squares_gpu.py		least_squares_gpu.py
least_squares_solve_cpu.py		least_squares_solve_cpu.py
line_fit_covariance.png		line_fit_covariance.png
lnprob_test_for_pytorch.ipynb		lnprob_test_for_pytorch.ipynb
pytorch_GP_least_squares_potrs.ipynb		pytorch_GP_least_squares_potrs.ipynb
pytorch_LS_covariance_performance.png		pytorch_LS_covariance_performance.png
y_fake.npy		y_fake.npy