← Search

Jonas Kübler

3 accepted papers

2022

Causal Inference Through the Structural Causal Marginal Problem

ICML 2022spotlight

We introduce an approach to counterfactual inference based on merging information from multiple datasets. We consider a causal reformulation of the statistical marginal problem: given a collection of marginal structural causal models (SCMs) over distinct but overlapping sets of variables, determine…

2020

Kernel Conditional Moment Test via Maximum Moment Restriction

UAI 2020poster

We propose a new family of specification tests called kernel conditional moment (KCM) tests. Our tests are built on a novel representation of conditional moment restrictions in a reproducing kernel Hilbert space (RKHS) called conditional moment embedding (CMME). After transforming the conditional mo…

2020

Learning Kernel Tests Without Data Splitting

NeurIPS 2020poster

Modern large-scale kernel-based tests such as maximum mean discrepancy (MMD) and kernelized Stein discrepancy (KSD) optimize kernel hyperparameters on a held-out sample via data splitting to obtain the most powerful test statistics. While data splitting results in a tractable null distribution, it s…