Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression

16 February 2021

Papers citing "Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression"

24 / 24 papers shown

Title
Optimizing Estimators of Squared Calibration Errors in Classification Sebastian G. Gruber Francis Bach 69 1 0 24 Feb 2025
Early Concept Drift Detection via Prediction Uncertainty Pengqian Lu Jie Lu Anjin Liu G. Zhang 79 0 0 15 Dec 2024
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 54 2 0 05 Nov 2024
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction Undral Byambadalai Tatsushi Oka Shota Yasui CML 34 0 0 22 Jul 2024
Neural-Kernel Conditional Mean Embeddings Eiki Shimizu Kenji Fukumizu Dino Sejdinovic 22 3 0 16 Mar 2024
Constructing Synthetic Treatment Groups without the Mean Exchangeability Assumption Yuhang Zhang Yue Liu Zhihua Zhang 13 0 0 28 Sep 2023
Towards Practicable Sequential Shift Detectors Oliver Cobb A. V. Looveren 13 0 0 27 Jul 2023
Learning sources of variability from high-dimensional observational studies Eric W. Bridgeford Jaewon Chung B. Gilbert Sambit Panda Adam Li Cencheng Shen A. Badea B. Caffo Joshua T. Vogelstein CML 13 3 0 26 Jul 2023
Asymptotically Unbiased Synthetic Control Methods by Density Matching Masahiro Kato Akari Ohda 42 1 0 20 Jul 2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models Tianyu Chen Kevin Bello Bryon Aragam Pradeep Ravikumar CML 22 1 0 30 Jun 2023
Causal survival embeddings: non-parametric counterfactual inference under censoring Carlos García-Meixide Marcos Matabuena CML 28 5 0 20 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 13 56 0 01 Jun 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 13 5 0 26 Apr 2023
Confidence and Uncertainty Assessment for Distributional Random Forests Jeffrey Näf Corinne Emmenegger Peter Buhlmann N. Meinshausen 22 3 0 11 Feb 2023
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 24 14 0 13 Dec 2022
Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects Jake Fawkes Robert Hu R. Evans Dino Sejdinovic OOD 18 3 0 09 Dec 2022
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect Stanislav R. Kirpichenko Lev V. Utkin A. Konstantinov CML 16 0 0 19 Nov 2022
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression A. Konstantinov Stanislav R. Kirpichenko Lev V. Utkin CML 16 3 0 19 Jul 2022
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Ronan Perry Julius von Kügelgen Bernhard Schölkopf 28 48 0 04 Jun 2022
Feature Selection for Discovering Distributional Treatment Effect Modifiers Yoichi Chikahara M. Yamada H. Kashima CML 11 5 0 01 Jun 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus M. Oprescu CML OOD 35 10 0 23 May 2022
Context-Aware Drift Detection Oliver Cobb A. V. Looveren 13 16 0 16 Mar 2022
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 27 6 0 04 Oct 2021
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 210 718 0 12 May 2016