Jonathan Lindbloom's repositories
gradient-projected-conjugate-gradient
A Python implementation of a conjugate gradient algorithm (GPCG) for solving bound-constrained quadratic programs.
rjpo-gaussian-sampling
A Python implementation of a reversible jump perturbation optimization (RJPO) method for sampling high-dimensional Gaussians.
randomized-trace-logdet-diag
Some Python implementations of randomized, matrix-free algorithms for estimating matrix traces, log determinants, diagonals, and diagonals of inverses.
regularization-toolkit
Some Python implementations of regularization parameter selection methods for regularized linear inverse problems.
running-stats
A simple Python module for computing the sample statistics of an array in a running/online fashion.
SMU-COVID-19
Some visualizations for SMU's COVID-19 case data, published here: https://blog.smu.edu/coronavirus-covid-19/cases/
arviz
Exploratory analysis of Bayesian models with Python
bayesian-projects
Just a collection of notebooks messing around with Bayesian models.
CTRPF-AR-CHEAT-CODES
[Database] CTRPF AR CHEAT CODES TO BE USED WITH CTRPF WITH ACTION REPLAY SUPPORT
dartlist-housing-visualization
Code for scraping Dartlist housing data to create a visualization.
jlindbloom.github.io
Personal website.
jlindbloom.github.io_old
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
computational-measure-transport
A repo for some measure transport examples.
dartmouth-acms
Source for Dartmouth's Applied and Computational Mathematics Seminar (ACMS) webpage.
GeneralizedSparsitySolvers
Code for the paper "Generalized sparsity-promoting solvers for Bayesian inverse problems".
hierarchical-solvers-for-inverse-problems
Some Python implementations of solvers for hierarchical Bayesian inverse problems.
iterative-method-viz
A repo for visualizing some iterative methods.
PE-MRF-Code
The code
pymc
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
simplekoopman
Some simple code for making a finite-rank approximation to a Koopman operator.
transformed-mcmc-example
A simple 1D example of doing MCMC in a transformed space to overcome multi-modality.
txcov19_inference
A work-in-progress model for COVID-19 infections in Texas taking vaccinations into account, built on PyMC3. Forked from the Priesemann Group's model.