quantile-regression 开源项目推荐（274 个）

ShangtongZhang /DeepRL

Modularized Implementation of Deep RL Algorithms in PyTorch

qfettes /DeepRL-Tutorials

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

henrikbostrom /crepes

Python package for conformal prediction

yromano /cqr

Conformalized Quantile Regression

cyoon1729 /RLcycle

A library for ready-made reinforcement learning agents and reusable components for neat prototyping

zillow /quantile-forest

Fast, scikit-learn-compatible quantile regression forests for prediction intervals and uncertainty estimation.

eliahuhorwitz /Conffusion

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

superlinear-ai /conformal-tights

👖 共形紧密算法为任何 scikit-learn 回归器或 Darts 预测器添加了相干分位数和区间的共形预测

FilippoMB /Ensemble-Conformalized-Quantile-Regression

Valid and adaptive prediction intervals for probabilistic time series forecasting.

liquidSVM /liquidSVM

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexi…

aangelopoulos /im2im-uq

Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

saattrupdan /doubt

Bringing back uncertainty to machine learning.

wwiecek /baggr

R package for Bayesian meta-analysis models, using Stan

RektPunk /MQBoost

[Mach. Learn. 2026] Official implementation of "Monotone Composite Quantile Regression via Second-Order Gradient Boosting Framework"

softmin /ReHLine

[NeurIPS 2023] Efficient Solver for ERM with PLQ Loss and Linear Constraints

RichardFindlay /day-ahead-probablistic-forecasting-with-quantile-regression

Using an integrated pinball-loss objective function in various recurrent based deep learning architectures made with keras to simultaneously produce probabilistic forecasts for UK wind, solar, demand and price forecasts.

getzze /RobustModels.jl

A Julia package for robust regressions using M-estimators and quantile regressions

Buczman /CaviaR

R code for CAViaR model

ErezSC42 /qr_forcaster

Our implementation of the paper "A Multi-Horizon Quantile Recurrent Forecaster"

lorismichel /quantregForest

R package - Quantile Regression Forests, a tree-based ensemble method for estimation of conditional quantiles (Meinshausen, 2006).