quantile-regression
There are 84 repositories under quantile-regression topic.
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
Conformal classifiers, regressors and predictive systems
cyoon1729/RLcycle
A library for ready-made reinforcement learning agents and reusable components for neat prototyping
yromano/cqr
Conformalized Quantile Regression
zillow/quantile-forest
Quantile Regression Forests compatible with scikit-learn.
eliahuhorwitz/Conffusion
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
FilippoMB/Ensemble-Conformalized-Quantile-Regression
Valid and adaptive prediction intervals for probabilistic time series forecasting
radix-ai/conformal-tights
š Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
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 flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
saattrupdan/doubt
Bringing back uncertainty to machine learning.
wwiecek/baggr
R package for Bayesian meta-analysis models, using Stan
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.
getzze/RobustModels.jl
A Julia package for robust regressions using M-estimators and quantile regressions
BayerSe/l1qr
Lasso Quantile Regression
ErezSC42/qr_forcaster
Our implementation of the paper "A Multi-Horizon Quantile Recurrent Forecaster"
Buczman/CaviaR
R code for CAViaR model
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.
dannysdeng/dqn-pytorch
PyTorch - Implicit Quantile Networks - Quantile Regression - C51
gcampanella/pydata-london-2018
Slides and notebooks for my tutorial at PyData London 2018
lorismichel/quantregForest
R packageĀ -Ā QuantileĀ RegressionĀ Forests, a tree-based ensemble method for estimation of conditional quantiles (Meinshausen, 2006).
CenterForAssessment/SGP
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 the coefficient matrices derived from the quantile regression analyses and specify what percentile growth is required for students to reach future achievement targets.
msesia/chr
Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
fmpr/DeepJMQR
Deep joint mean and quantile regression for spatio-temporal problems
SSS135/aiqn-vae
VAE + Quantile Networks for MNIST
TeaPearce/Censored_Quantile_Regression_NN
NeurIPS paper 'Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis'
CY-dev/hqreg
Regularization Paths for Huber Loss Regression and Quantile Regression Penalized by Lasso or Elastic-Net
opardo/GPDPQuantReg
R Package. Bayesian and nonparametric quantile regression, using Gaussian Processes to model the trend, and Dirichlet Processes, for the error. Author: Carlos Omar Pardo Gomez.
yatshunlee/CAViaR
Measure market risk by CAViaR model
adrian-lison/interval-scoring
This repository contains python implementations of scoring rules for forecasts provided in a prediction interval format.
elifyilmaz2027/traffic_flow_forecasting_methods
The repository gives case studies on short-term traffic flow forecasting strategies within the scope of my master thesis.
Jbrich95/pinnEV
Partially-Interpretable Neural Networks for Extreme Value modelling
anhdanggit/non-parametric-econometrics
This is the R code for several common non-parametric methods (kernel est., mean regression, quantile regression, boostraps) with both practical applications on data and simulations
fboehm/openFHDQR
Open-source implementation of ADMM algorithms for penalized quantile regression in Gu, et al. 2018 Technometrics
jobstdavid/gamvinereg
D-Vine GAM Copula based Quantile Regression
be-green/quantspace
R package for estimating quantile regression coefficients via the quantile spacing method