quantile-regression topic
Conffusion
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
Ensemble-Conformalized-Quantile-Regression
Valid and adaptive prediction intervals for probabilistic time series forecasting
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.
qr_forcaster
Our implementation of the paper "A Multi-Horizon Quantile Recurrent Forecaster"
crepes
Python package for conformal prediction
chr
Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
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...
dqn-pytorch
PyTorch - Implicit Quantile Networks - Quantile Regression - C51
quantregForest
R package - Quantile Regression Forests, a tree-based ensemble method for estimation of conditional quantiles (Meinshausen, 2006).
SGP
Functions to calculate student growth percentiles and percentile growth projections/trajectories for students using large scale, longitudinal assessment data. Functions use quantile regressi...