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Distribution Shift Python Packages

Python packages with the GitHub topic distribution-shift. Sorted by monthly downloads, with stars and forks.
IFCA-Advanced-Computing
frouros

Frouros: an open-source Python library for drift detection in machine learning systems.

3K 260 20
awesomedudeworld13
benchgap

Measure how much of a machine-learning benchmark score survives deployment. Grouped bootstrap, frozen thresholds, gap attribution.

492 1 0
DiogoRibeiro7
population-resemblance

Python library for monitoring categorical population drift with the Population Resemblance Statistic (PRS), sample-size-aware thresholds, PSI and discrete KS benchmarks, and Monte Carlo simulation.

369 0 0
chrisyeh96
sustaingym

Reinforcement Learning Environments for Sustainable Energy Systems

258 72 16
namkoong-lab
whyshift

A python package providing a benchmark with various specified distribution shift patterns.

251 62 4
vkhamesi
ocpdet

📦 A Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach based on neural networks.

250 35 4
kevinsbello
iscan-dag

A Python 3 package for identifying distribution shifts (a.k.a feature-shifts) between datasets. Official implementation of the paper: "iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models".

203 6 2
RichardObi
frd-score

Official implementation of the Fréchet Radiomic Distance

189 36 3
burning-cost
insurance-covariate-shift

Density ratio correction for insurance pricing book shifts — CatBoost/RuLSIF/KLIEP, LR-QR conformal, FCA SUP 15.3 diagnostics

160 0 0
biquality-learn
biquality-learn

A Python Library for Biquality Learning

150 17 1
steverab
incerto

A comprehensive library for uncertainty quantification in machine learning.

77 1 0
EdisonLeeeee
greatx

A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).

64 89 12
EdisonLeeeee
graphwar

A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).

60 89 12
divelab
graph-ood

GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]

50 212 22
finite-sample
winference

Calibrating pairwise rankings with accomodations for non-transitivity

44 1 0
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