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arxiv.py

Python wrapper for the arXiv API

awesome-conformal-prediction

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

black-box-quantile-kernels

The authors' code for paper "Black Box Quantiles for Kernel Learning" Tompkins et al. AISTATS 2019

causal-learn

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

causaldiscoverytoolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

causality-molak-repo

Notes, exercises and other materials related to causal inference, causal discovery and causal ML.

causalxtreme

An R package for causal discovery in heavy-tailed models

cdml-neurips2020

This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop at Neural Information Processing Systems (NeurIPS) 2020.

collider-regression

This repo contains material for the paper "Returning the Favour: When Regression Benefits from Probabilistic Causal Knowledge" ICML 2023 paper

conformal-prediction

Lightweight, useful implementation of conformal prediction on real data.

coveralls-python

Show coverage stats online via coveralls.io

deepobs

The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

extremevaluemachine

This is an implementation of the Extreme Value Machine by Rudd et al., with minor changes from the original work.

gpar

Implementation of the Gaussian Process Autoregressive Regression Model

graphicalextremes

Statistical methodology for graphical extreme value models

heteroskedasticconformalregression

Paper HeteroskedasticConformalRegression

instrumental-variable-regression-via-kernel-maximum-moment-loss

Python implementation of Kernel Maximum Moment Restriction for Instrumental Variable Regression

kcipt

Kernel Conditional Independence Permutation Test

kernel-instrumental-variable-regression

Kernel Instrumental Variable Regression

kernel-mixture-of-polynomials

R code for posterior inference in kernel mixture of polynomials for nonparametric regression and partial linear model

kernelized-cumulants

kernelsoperatorlearning

Code for "Kernel methods are competitive for operator learning" Battle, Darcy. Hosseini and Owhadi.

lp-ci-test

machine_learning_refined

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

natural-language-processing-a-machine-learning-perspective

pgmpy

Python Library for Inference (Causal and Probabilistic) and learning in Bayesian Networks

priorvae

Code of PriorVAE: encoding spatial priors with variational autoencoders

py-causal

pylimitbook

Python implementation of fast limit-order book.