quantile-regression

Modularized Implementation of Deep RL Algorithms in PyTorch

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

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

Conformalized Quantile Regression

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

Conformal regressors and predictive systems

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…

Valid and adaptive prediction intervals for probabilistic time series forecasting

R package for Bayesian meta-analysis models, using Stan

Bringing back uncertainty to machine learning.

Quantile Regression Forests compatible with scikit-learn.

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.

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

Slides and notebooks for my tutorial at PyData London 2018

Lasso Quantile Regression

PyTorch - Implicit Quantile Networks - Quantile Regression - C51

Functions to calculate student growth percentiles and percentile growth projections/trajectories for students using large scale, longitudinal assessment data. Functions use quantile regression to estimate the conditional density associated with each student's achievement history. Percentile growth projections/trajectories are calculated using th…

R code for CAViaR model

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

Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems