johnny-godoy

coverage

GitHub Action for python coverage publish & analysis

pykan

Kolmogorov Arnold Networks

marimo

A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.

fastapprox

Approximate and vectorized versions of common mathematical functions

PiML-Toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

mdlrnn-torch

Minimum Description Length Recurrent Neural Networks (MDLRNNs) in PyTorch

orthogonal-additive-gaussian-processes

Light-weighted code for Orthogonal Additive Gaussian Processes

doubleml-for-py

DoubleML - Double Machine Learning in Python

nllf-emnlp-2023

This is the official repo for Deep Natural Language Feature Learning for Interpretable Prediction @ EMNLP 2023.

PaCMAP

PaCMAP: Large-scale Dimension Reduction Technique Preserving Both Global and Local Structure

xai

XAI - An eXplainability toolbox for machine learning

pmlb

PMLB: A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms.

nodegam

Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"

ferret

A python package for benchmarking interpretability techniques on Transformers.

xcon

exaggerated-safety

Röttger et al. (2023): "XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models"

node

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

ProtoPNet

This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT Lincoln Laboratory), and Cynthia Rudin (Duke University) (* denotes equal contribution).

text-knnassifier

A tool for compressed KNN text classification

awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

beartype

Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.

mrmr

mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

Pottslab

Unsupervised multilabel image segmentation (color/gray/multichannel) based on the Potts model (aka piecewise constant Mumford-Shah model)

gosdt-guesses

Generalized Optimal Sparse Decision Trees

fastSparse

flam

:exclamation: This is a read-only mirror of the CRAN R package repository. flam — Fits Piecewise Constant Models with Data-Adaptive Knots

SparseLogisticPCA-Python

An unofficial Python implementation of the Sparse Logistic PCA from "Sparse logistic principal components analysis for binary data"

pycorels

Public home of pycorels, the python binding to CORELS

EC-Bestiary

A bestiary of evolutionary, swarm and other metaphor-based algorithms