Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
| import torch | |
| import gpytorch | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| torch.manual_seed(42) | |
| np.random.seed(42) | |
| ## Simulate hierarchical Data ## |
| from jax import random, jit | |
| import jax.numpy as jnp | |
| from jax.scipy import stats | |
| from util import ravelize_function, make_log_density | |
| __all__ = ["log_density", "log_density_vec", "init_draw_zero"] | |
| def constrain_parameters(sigma_unc, alpha, beta): |
| """ | |
| Python code to generate M-splines and I-splines. | |
| References | |
| ---------- | |
| Ramsay, J. O. (1988). Monotone regression splines in action. | |
| Statistical science, 3(4), 425-441. | |
| """ | |
| import numpy as np |