PaCMAP for Dimension Reduction
(code) | (paper)

Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models
(code) | (paper)

FLAME - Fast Large Almost Matching Exactly
DAME - Dynamic Almost Matching Exactly
FLAME-IV - Almost Matching Exactly with Instrumental Variables
MALTS - Matching After Learning to Stretch
AHB - Adaptive Hyperboxes
(code) | (CRAN site)

For large scale interpretable matching in causal inference.

Generalized and Scalable Optimal Sparse Decision Trees (GOSDT)
(code) | (benchmarking) | (paper) | (bib)

Concept Whitening
(code) | (paper)

Photo Upsampling via Latent Space Exploration of Generative Models (PULSE)
(project page with code and online demo) | (paper)

Age of Unfairness
(code) | (paper)

Interpretable Prototype Neural Networks (This Looks Like That)
(code) | (bib) | (paper)

Interpretable Deep Neural Networks with Hierarchical Prototypes
(code) | (paper)

Globally Consistent Summary-Explanations
(code) | (paper)

ROC Flexibility Data
Used for several ranking papers (data)

MCR - Model Class Reliance
(code) | (paper)

For assessing variable importance of a model class for a dataset.

Optimal Sparse Decision Trees (OSDT)
(code) | (paper)

Predecessor to GOSDT (above).

Superresolution Code from 2018 NTIRE Competition
(Webster and McCourt's code) | (Alex, Sachit, and Nikhil's code) | (paper)

Recovery Curves
(code) | (paper)

Higher Dimensional Histograms
(code) | (paper) | (bib)

For density trees and density rule lists.

Causal SVM
(code) | (paper)

For estimating whether personalized treatment effects are positive, negative or neutral.

Regulating Greed Over Time
(code) | (paper)

Interpretable Prototype Neural Networks from 2017 (our latest paper on this topic is better, see above)
(code) | (bib) | (paper)

Optimized Falling Rule Lists and Softly Falling Rule Lists
(paper) | (code) | (bib)

For classification where the probabilities decrease along the list.

Series Finder
(code) | (paper)

For detecting crime series.

Actionable and Interpretable Treatment Regimes (CITR)
(code) | (paper)

For creating a policy. Uses causal inference, includes costs of gathering information, treatment, and effectiveness of the treatment.

Certifiably Optimal RulE ListS (CORELS)
(code) | (R-bindings by Dirk Eddelbuettel) (paper)

For classification, an alternative to decision trees. Not Bayesian, but with proof of optimality.

Learning Optimized Risk Scores from Large-Scale Datasets (RiskSLIM)
(code) | (paper)

Creates risk assessment scoring systems.

Interpretable Models for Recidivism Prediction
(code for processing raw data) | (code for machine learning pipeline) | (paper)

For reproducibility of JRSS-A paper from 2015-2016. SLIM code is below.

ClusteR-specific Assorted Feature selecTion (CRAFT)
(code) | (paper)

Clustering with cluster-specific feature selection.

Scalable Bayesian Rule Lists (SBRL)
(R interface, C code - Creative Commons License) | (paper) | (bib)

For classification, an alternative to decision trees. Faster than BRL. Predecessor of CORELS (above).

Bayesian Case Model (BCM)
(code) | (paper)

Prototype clustering with cluster-specific feature selection.

Box Drawings for Learning with Imbalanced Data
(matlab code) | (paper) | (bib)

For imbalanced classification with real-valued features.

Bayesian Rule Lists (BRL)
(python code - MIT license) | (paper) | (bib)

For classification, an alternative to decision trees. This is a predecessor of SBRL and CORELS (above).

Bayesian Or's of And's
(code and coupon data) | (data on UCI repo) | (paper) | (bib) | (code by Ritwik Mitra, Emily Dodwell, Elena Khusainova, Deirdre Paul)

For classification, an alternative to decision trees, inductive logic programming and associative classification.

Supersparse Linear Integer Models (SLIM)
(matlab code) | (python code) | (matlab code) | (paper) | (bib)

For building scoring systems, which are linear models with integer coefficients. Part of winning entry for 2016 INFORMS Innovative Applications in Analytics Award.

Falling Rule Lists (FRL)
(python code) | (paper) | (bib)

For classification where the probabilities decrease along the list.

Growing a List
(python code) | (paper) | (bib)

A search engine that performs set expansion. Note that this code is artificially slowed down by a restriction on the number of queries per minute, imposed by search engine companies. Unrestricted access to a search engine would eliminate this issue.

On Combining Machine Learning with Decision Making
(code) | (paper) | (bib)

For new decision making framework.