Cover Image

Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Singh, Rahul, Xu, Liyuan, Gretton, Arthur
Format:	Preprint
Published:	2021
Subjects:	Methodology Machine Learning Econometrics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Nonparametric Instrumental Variable Analysis Without Structural Equations: Debiased Inference on Functionals of Inverse Problems with No Solutions
by: Shen, Zikai, et al.
Published: (2026)

TEA-Time: Transporting Effects Across Time
by: Parikh, Harsh, et al.
Published: (2026)

Causal Mediation Analysis with Multiple Mediators: A Simulation Approach
by: Zhou, Jesse, et al.
Published: (2025)

A Gentle Introduction to Conformal Time Series Forecasting
by: Stocker, M., et al.
Published: (2025)

Identifying Elasticities in Autocorrelated Time Series Using Causal Graphs
by: Tiedemann, Silvana, et al.
Published: (2024)

Program Evaluation with Remotely Sensed Outcomes
by: Rambachan, Ashesh, et al.
Published: (2024)

A Large-Scale Empirical Comparison of Meta-Learners and Causal Forests for Heterogeneous Treatment Effect Estimation in Marketing Uplift Modeling
by: Singh, Aman
Published: (2026)

Transfer Learning for Spatial Autoregressive Models with Application to U.S. Presidential Election Prediction
by: Zeng, Hao, et al.
Published: (2024)

Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing
by: Yan, Jian, et al.
Published: (2022)

Near-Optimal Non-Parametric Sequential Tests and Confidence Sequences with Possibly Dependent Observations
by: Bibaut, Aurelien, et al.
Published: (2022)

Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints
by: Sakaguchi, Shosei
Published: (2021)

Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits
by: Zhan, Ruohan, et al.
Published: (2021)

Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities
by: Chen, Xiaohong, et al.
Published: (2021)

Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
by: Nagai, Tomoko, et al.
Published: (2024)

Formalising causal inference as prediction on a target population
by: Höltgen, Benedikt, et al.
Published: (2024)

Functional effects models: Accounting for preference heterogeneity in panel data with machine learning
by: Salvadé, Nicolas, et al.
Published: (2025)

Vector Copula Variational Inference and Dependent Block Posterior Approximations
by: Fu, Yu, et al.
Published: (2025)

Robust Matrix Estimation with Side Information
by: Agarwal, Anish, et al.
Published: (2026)

Fast Online Changepoint Detection
by: Ghezzi, Fabrizio, et al.
Published: (2024)

Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)

Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach
by: Si, Nian
Published: (2023)

A step towards the integration of machine learning and classic model-based survey methods
by: Żądło, Tomasz, et al.
Published: (2024)

Machine-Learning-Assisted Comparison of Regression Functions
by: Yan, Jian, et al.
Published: (2025)

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
by: Agarwal, Abhineet, et al.
Published: (2023)

An Introduction to Double/Debiased Machine Learning
by: Ahrens, Achim, et al.
Published: (2025)

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
by: Chen, Hongyu, et al.
Published: (2026)

Linear Multidimensional Regression with Interactive Fixed-Effects
by: Freeman, Hugo
Published: (2022)

Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal
by: Athey, Susan, et al.
Published: (2023)

xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R
by: Polselli, Annalivia
Published: (2025)

HMM-LSTM Fusion Model for Economic Forecasting
by: Sivakumar, Guhan
Published: (2025)

Synthetic Potential Outcomes and Causal Mixture Identifiability
by: Mazaheri, Bijan, et al.
Published: (2024)

Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
by: Adedayo, S. A.
Published: (2025)

Estimating Causal Effects with Double Machine Learning -- A Method Evaluation
by: Fuhr, Jonathan, et al.
Published: (2024)

Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators
by: Klaassen, Sven, et al.
Published: (2025)

Adaptive stable distribution and Hurst exponent by method of moments moving estimator for nonstationary time series
by: Duda, Jarek
Published: (2025)

Covariate-Adjusted Deep Causal Learning for Heterogeneous Panel Data Models
by: Zhou, Guanhao, et al.
Published: (2025)

A Causal Inference Framework for Data Rich Environments
by: Abadie, Alberto, et al.
Published: (2025)

Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation
by: Akgun, Oguzhan, et al.
Published: (2025)

Adaptive Student's t-distribution with method of moments moving estimator for nonstationary time series
by: Duda, Jarek
Published: (2023)

On Binscatter
by: Cattaneo, Matias D., et al.
Published: (2019)