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@GStechschulte
GStechschulte / hierarchical_gpytorch.py
Created June 18, 2025 15:27
Hierarchical Gaussian process model with GPyTorch
import torch
import gpytorch
import numpy as np
import matplotlib.pyplot as plt
torch.manual_seed(42)
np.random.seed(42)
## Simulate hierarchical Data ##
@WardBrian
WardBrian / linear_regression.py
Last active November 5, 2025 17:16
functional-style jax models (take 2)
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):
@naturale0
naturale0 / splines.py
Last active July 21, 2025 21:55 — forked from ahwillia/msplines.py
Generate M-spline and I-spline functions in Python
"""
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
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@veekaybee
veekaybee / normcore-llm.md
Last active November 20, 2025 15:04
Normcore LLM Reads

Anti-hype LLM reading list

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.

Foundational Concepts

Screenshot 2023-12-18 at 10 40 27 PM

Pre-Transformer Models

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