Copertina

Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pettersson, Markus B., Jerzak, Connor T., Daoud, Adel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning 62C12 H.3
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Scoping Review of Earth Observation and Machine Learning for Causal Inference: Implications for the Geography of Poverty
di: Sakamoto, Kazuki, et al.
Pubblicazione: (2024)

Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
di: Jerzak, Connor T., et al.
Pubblicazione: (2025)

Effect Heterogeneity with Earth Observation in Randomized Controlled Trials: Exploring the Role of Data, Model, and Evaluation Metric Choice
di: Jerzak, Connor T., et al.
Pubblicazione: (2024)

Chinese vs. World Bank Development Projects: Insights from Earth Observation and Computer Vision on Wealth Gains in Africa, 2002-2013
di: Daoud, Adel, et al.
Pubblicazione: (2025)

Inference for overparametrized hierarchical Archimedean copulas
di: Perreault, Samuel, et al.
Pubblicazione: (2024)

A new multivariate Poisson model
di: Murphy, Orla A., et al.
Pubblicazione: (2024)

Causal discovery under mean independence and linearity
di: Mesters, Geert, et al.
Pubblicazione: (2026)

Laplace Variational Inference for Bayesian Envelope Models
di: Kim, Seunghyeon, et al.
Pubblicazione: (2026)

On the spherical cardioid distribution and its goodness-of-fit
di: García-Portugués, Eduardo
Pubblicazione: (2026)

On spectral clustering under non-isotropic Gaussian mixture models
di: Kawamoto, Kohei, et al.
Pubblicazione: (2026)

Bayesian Benefit-Risk Assessment with Dependent Outcomes via Latent Factor Models
di: Vamvourellis, Konstantinos, et al.
Pubblicazione: (2022)

Reduced-Rank Autoregressive Model for High-Dimensional Multivariate Network Time Series
di: Lyu, Qi, et al.
Pubblicazione: (2026)

Estimation of Directed Acyclic Graphs by Frequentist Model Averaging
di: Liu, Huihang, et al.
Pubblicazione: (2026)

Directional $ρ$-coefficients
di: de Amo, Enrique, et al.
Pubblicazione: (2025)

Fast convergence of a Federated Expectation-Maximization Algorithm
di: Tao, Zhixu, et al.
Pubblicazione: (2024)

Sparse PCA: Phase Transitions in the Critical Regime
di: Feldman, Michael J., et al.
Pubblicazione: (2024)

Subspace decompositions for association structure learning in multivariate categorical response regression
di: Zhao, Hongru, et al.
Pubblicazione: (2024)

Can Large Language Models (or Humans) Disentangle Text?
di: de Pieuchon, Nicolas Audinet, et al.
Pubblicazione: (2024)

The optimal Padé polynomial for reconstruction of luminosity distance based on 10-fold cross-validation
di: Yu, Bo, et al.
Pubblicazione: (2025)

Statistical and Machine Learning Analysis of Traffic Accidents on US 158 in Currituck County: A Comparison with HSM Predictions
di: Sawyer, Jennifer, et al.
Pubblicazione: (2025)

Asymptotic bias reduction of maximum likelihood estimates via penalized likelihoods with differential geometry
di: Hirose, Masayo Y., et al.
Pubblicazione: (2020)

Statistical Inference for Low-Rank Tensor Models
di: Xu, Ke, et al.
Pubblicazione: (2025)

Leveraging Compact Satellite Embeddings and Graph Neural Networks for Large-Scale Poverty Mapping
di: Pettersson, Markus B., et al.
Pubblicazione: (2025)

On the spherical Laplace distribution
di: You, Kisung, et al.
Pubblicazione: (2022)

Asymptotics for non-degenerate multivariate $U$-statistics with estimated nuisance parameters under the null and local alternative hypotheses
di: Desgagné, Alain, et al.
Pubblicazione: (2024)

A General Bayesian Nonparametric Approach for Estimating Population-Level and Conditional Causal Effects
di: Hur, Yongseok, et al.
Pubblicazione: (2025)

Clustering Multivariate Time Series using Energy Distance
di: Davis, Richard A., et al.
Pubblicazione: (2023)

Controlling the False Discovery Rate in Subspace Selection
di: Díaz, Mateo, et al.
Pubblicazione: (2024)

Omnibus goodness-of-fit tests for univariate continuous distributions based on trigonometric moments
di: Desgagné, Alain, et al.
Pubblicazione: (2025)

Inference in high-dimensional logistic regression under tensor network dependence
di: Miles, Josh, et al.
Pubblicazione: (2026)

Spectral embedding and the latent geometry of multipartite networks
di: Modell, Alexander, et al.
Pubblicazione: (2022)

Parametric Bootstrap for Fixed Edge-Probability Network Models
di: Shao, Zhixuan, et al.
Pubblicazione: (2024)

Minimum Covariance Determinant Estimator and Outlier Detection for Interval-valued Data
di: Loureiro, Catarina P., et al.
Pubblicazione: (2026)

Information criteria for the number of directions of extremes in high-dimensional data
di: Butsch, Lucas, et al.
Pubblicazione: (2024)

A novel framework for detecting multiple change points in functional data sequences
di: Fang, Zhiqing, et al.
Pubblicazione: (2025)

Conformal Prediction for Hierarchical Data
di: Principato, Guillaume, et al.
Pubblicazione: (2024)

A Modified Bayesian Criterion for Model Selection in Mixed and Hierarchical Frameworks
di: Ramirez, Diogenes de Jesus, et al.
Pubblicazione: (2026)

Graphical lasso for extremes
di: Wan, Phyllis, et al.
Pubblicazione: (2023)

Multivariate MM-estimators with auxiliary Scale for Linear Models with Structured Covariance Matrices
di: Lopuhaa, Hendrik Paul
Pubblicazione: (2025)

Statistical inference for extremal directions in high-dimensional spaces
di: Butsch, Lucas, et al.
Pubblicazione: (2026)