idc9

py_jive

A data analysis package for high-dimensional, multi-block data.

stor390

Introduction to Data Science

mvdr

A python package for multi-view dimensionality reduction

ya_pca

Yet another PCA package. This one focuses on rank selection.

jackstraw

implements jackstraw methods in python test for associations between variables and systematic modes of variation discovered in the data.

r_jive

Implementation of AJIVE in R

breast_cancer_image_analysis

Reproduces the analysis from Carmichael et al. 2019

NetworkChangePoint

Nonparametric change point detection for growing trees and code to reproduce figures in Banerjee, Bhamidi and Carmichael, 2018

word_embed_tutorial

tutorial on getting started with word embeddings in python using Supreme Court opinions

FalseConfidence

Code to reproduce figures in Carmichael and Williams, 2018

idc9.github.io

Personal website

mvmm

Learning sparsity and block diagonal structure in multi-view mixture models.

what_the_cluster

Python implementation of some algorithms to determine the "optimal" number of clusters

andersoncd

Implementation of Anderson acceleration of coordinate descent.

course-materials

courtlistener

A free and powerful system for awareness and research of the American judicial system.

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

diproperm

DiProPerm for high dimensional hypothesis testing.

ds_tutorials

data science tutorials

explore

tools for exploratory data analysis

fclsp

Folded concave Laplacian spectral penalization.

graspy

Python package for graph statistics

HistomicsTK

A Python toolkit for pathology image analysis algorithms.

lightning

Deep learning framework to train, deploy, and ship AI products Lightning fast.

mvlearn

Python package for multi-view machine learning

mvmm_sim

Reproduces the simulations from Carmichael, 2020.

repro_homelessness_retention_atp

Reproduce the results of "Patient Characteristics and Retention Among Unhoused Patients Enrolled in a Low-Barrier-To Treatment Entry Opioid Agonist Program"

repro_lap_reg

Reproduces the result from the Laplacian regularization paper (Carmichael, 2021)

SimpleParsing

Simple, Elegant, Typed Argument Parsing with argparse

UNC_science_expo_2018

Interactive Shiny Applicatino in R to demonstrate the hazards of spurious correlations. App can be found at https://cbreen.shinyapps.io/final_app/