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A stand-alone implementation of several NumPy dtype extensions used in machine learning.
Code for the paper E. Raninen and E. Ollila, “Coupled regularized sample covariance matrix estimator for multiple classes,” in IEEE Transactions on Signal Processing, vol. 69, pp. 5681–5692, 2021, …
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💥 Fast matrix-multiplication as a self-contained Python library – no system dependencies!
Benchmarking matrix multiplication implementations
Gradient descent methods for Bayesian variational inference with mean field approximation.
A library of standard population genetic models
A new model and algorithm for multivariate Bayesian variable selection regression.
ldshrink: a one-stop R package for shrinkage estimation of linkage disequilibrium
🏊 Individual-Level, Summary-Level and Single-Step Bayesian Regression Models for Genomic Prediction and Genome-Wide Association Studies
Towards Efficient Discrete Integration via Adaptive Quantile Queries
Experimental tool for approximating high dimensional combinatorics
Exact optimization for cost function networks and additive graphical models
R-package for structural equation modeling based on GWAS summary data
Simulate genealogical trees and genomic sequence data using population genetic models
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Fast EM algorithm for a Probabilistic PCA model for Genotype data
Exercises and notes on Structure and Interpretation of Classical Mechanics.
Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.