confounding

Confound-isolating cross-validation approach to control for a confounding effect in a predictive model.

Conquering confounds and covariates: methods, library and guidance

NeurIPS 2024 (spotlight): A Textbook Remedy for Domain Shifts Knowledge Priors for Medical Image Analysis

☯︎[ACMMM'22] Official PyTorch Implementation of Towards Unbiased Visual Emotion Recognition via Causal Intervention

A library for minimizing the effects of confounding covariates

Shiny-Tool for investigation of metabolite-covariate relationships

SNP abundance correlates with network degree

Learn causal inference by changing the world. Guided lessons and a sandbox with confounders, mediators, colliders, and six estimators, live in the browser

DAG Builder

Accounting for hidden confounders in estimates of dose-response curves from observational data.

CLI that applies the Clever Materials falsification test to materials-science ML datasets: detects confounding via a bibliographic fingerprint (year/author/journal leaking the target). Built on Jablonka 2026 (arXiv:2602.17730) + Huang&Cole / Nandy datasets (Scientific Data).

An R-Package to perform Time-Dependent Matching for Causal Inference in Discrete and Continuous Time

Code for a probabilistic sensitivity analysis of an unmeasured confounder

Source code for off-policy evaluation and optimization in the presence of unobserved confounding, accepted to AISTATS 2024.

Open-source causal audit engine for claim verification: d-separation & backdoor adjustment, 22-bias catalog, PubMed evidence with real PMIDs, hallucination-resistant red team. TypeScript, zero runtime deps.

End-to-end empirical implementation of model-based off-policy evaluation and pessimistic policy selection for confounded POMDPs (Hong, Qi & Xu, ICML 2024)

Confounding issues in air pollution epidemiology: an empirical assessment with the UK Biobank cohort

Recurrence risk of remedial actions on real openFDA MAUDE data. A null result, and the target-leakage episode that produced the wrong answer first.

blopmatch: Matching Estimator based on a Bilevel Optimization Problem

Test (un)confoundedness by comparing an effect from an RCT-like dataset to the same estimand from an observational dataset. Supports IPW/AIPW, bootstrap CIs, a Wald test, and optional transportability weighting (manual or auto-detected via KS/energy tests).