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Iain Carmichael's Projects

andersoncd icon andersoncd

Implementation of Anderson acceleration of coordinate descent.

courtlistener icon courtlistener

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

deep-learning-v2-pytorch icon deep-learning-v2-pytorch

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

diproperm icon diproperm

DiProPerm for high dimensional hypothesis testing.

explore icon explore

tools for exploratory data analysis

fclsp icon fclsp

Folded concave Laplacian spectral penalization.

graspy icon graspy

Python package for graph statistics

histomicstk icon histomicstk

A Python toolkit for pathology image analysis algorithms.

jackstraw icon jackstraw

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

law-net icon law-net

code to analyze the legal citation network

lightning icon lightning

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

mvdr icon mvdr

A python package for multi-view dimensionality reduction

mvlearn icon mvlearn

Python package for multi-view machine learning

mvmm icon mvmm

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

mvmm_sim icon mvmm_sim

Reproduces the simulations from Carmichael, 2020.

networkchangepoint icon networkchangepoint

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

plot_ellipse icon plot_ellipse

An easy-to-use function for plotting ellipses in Python 2.7 with matplotlib

py_jive icon py_jive

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

repro_homelessness_retention_atp icon 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 icon repro_lap_reg

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

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