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Periodic Reporting for period 4 - CausalStats (Statistics, Prediction and Causality for Large-Scale Data)

Project: CausalStats

Updated at: 01-10-2024

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Project acronym CausalStats

Double machine learning methods: Beyond independence

Project: CausalStats

Updated at: 01-10-2024

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Project acronym CausalStats

Change point detection algorithms and methodology for large-scale data

Project: CausalStats

Updated at: 01-10-2024

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Project acronym CausalStats

Anchor regression: Heterogeneous Data Meet Causality

Project: CausalStats

Updated at: 03-08-2024

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Project acronym CausalStats

A Rank-Based Sequential Test of Independence

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Model selection over partially ordered sets

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

TSCI: two stage curvature identification for causal inference with invalid instruments

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Invariant Probabilistic Prediction

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Random Forests for Change Point Detection

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

"Discussion of ""A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models"""

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Distributionally Robust and Generalizable Inference

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Treatment Effect Estimation with Observational Network Data using Machine Learning

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Confidence and Uncertainty Assessment for Distributional Random Forests

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Regularized Double Machine Learning in Partially Linear Models with UnobservedConfounding

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Distributionally Robust Machine Learning with Multi-source Data

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

ricu: R’s interface to intensive care data

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a...

Project: CausalStats

Updated at: 14-05-2024

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Project acronym CausalStats

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Regularizing Double Machine Learning in Partially Linear Endogenous Models

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Identifying cancer pathway dysregulations using differential causal effects

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Stabilizing variable selection and regression

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Invariance, Causality and Robustness

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Deconfounding and causal regularization for stability and external validity

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Seeded binary segmentation: a general methodology for fast and optimal changepoint detection

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Double-estimation-friendly inference for high-dimensional misspecified models

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Distributional anchor regression

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Higher-order least squares: assessing partial goodness of fit of linear causal models

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

One Modern Culture of Statistics: Comments on Statistical Modeling: The Two Cultures (Breiman, 2001b)

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

Change point detection for graphical models in presence of missing values

Project: CausalStats

Updated at: 27-04-2024

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Project acronym CausalStats

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Periodic Reporting for period 4 - CausalStats (Statistics, Prediction and Causality for Large-Scale Data)

Double machine learning methods: Beyond independence

Change point detection algorithms and methodology for large-scale data

Anchor regression: Heterogeneous Data Meet Causality

A Rank-Based Sequential Test of Independence

Model selection over partially ordered sets

TSCI: two stage curvature identification for causal inference with invalid instruments

Invariant Probabilistic Prediction

Random Forests for Change Point Detection

"Discussion of ""A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models"""

Distributionally Robust and Generalizable Inference

Treatment Effect Estimation with Observational Network Data using Machine Learning

Confidence and Uncertainty Assessment for Distributional Random Forests

Regularized Double Machine Learning in Partially Linear Models with UnobservedConfounding

Distributionally Robust Machine Learning with Multi-source Data

ricu: R’s interface to intensive care data

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a...

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

Regularizing Double Machine Learning in Partially Linear Endogenous Models

Identifying cancer pathway dysregulations using differential causal effects

Stabilizing variable selection and regression

Invariance, Causality and Robustness

Deconfounding and causal regularization for stability and external validity

Seeded binary segmentation: a general methodology for fast and optimal changepoint detection

Double-estimation-friendly inference for high-dimensional misspecified models

Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding

Distributional anchor regression

Higher-order least squares: assessing partial goodness of fit of linear causal models

One Modern Culture of Statistics: Comments on Statistical Modeling: The Two Cultures (Breiman, 2001b)

Change point detection for graphical models in presence of missing values