AI Paper Atlas

Research map / Probabilistic and scientific modeling / Treatment effects

Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects

NeurIPS 2020 · Probabilistic and scientific modeling › Treatment effects · approach: Meta-learners and partial identification · 6 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use covariate-matched differences with pseudo-observations rather than separately estimating and differencing the baselinesHTE estimation · Random-design numerical experimentsRMSEHelped
Discard control-treatment pairs with poor matching quality instead of retaining all matched pairs (ablation)Selected matching estimator · Random-design numerical experiments as d or κ increasesRMSEHelped
Retain all matched pairs (set m2=m1) rather than selecting the pairs with the best matching distances (ablation)Selected matching estimator · Random-design numerical experiments as d or κ increasesRMSEHurt
Retain all matched pairs (set m2=m1) rather than selecting the pairs with the best matching distances (ablation)Selected matching estimator · Random-design numerical experiments with d=κ=1RMSENo clear effect

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy