Image de couverture de livre

Double Machine Learning for Adaptive Causal Representation in High-Dimensional Data

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Aouar, Lynda, Yu, Han
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Applications Computation
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Causal Inference with Double/Debiased Machine Learning for Evaluating the Health Effects of Multiple Mismeasured Pollutants
par: Xu, Gang, et autres
Publié: (2024)

fastHDMI: Fast Mutual Information Estimation for High-Dimensional Data
par: Yang, Kai, et autres
Publié: (2024)

Causal Representation Learning with Generative Artificial Intelligence: Application to Texts as Treatments
par: Imai, Kosuke, et autres
Publié: (2024)

Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
par: More, Sushant, et autres
Publié: (2024)

Semi-Parametric Bayesian Additive Regression Trees for Risk Prediction with High-Dimensional Epigenetic Signatures and Low-Dimensional Covariates
par: Bhandari, Saurabh, et autres
Publié: (2026)

Subjective Perspectives within Learned Representations Predict High-Impact Innovation
par: Cao, Likun, et autres
Publié: (2025)

Feature Augmentations for High-Dimensional Learning
par: Zhu, Xiaonan, et autres
Publié: (2025)

A Novel Framework for Analyzing Structural Transformation in Data-Constrained Economies Using Bayesian Modeling and Machine Learning
par: Katende, Ronald
Publié: (2024)

Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm
par: Luo, Nanyu, et autres
Publié: (2025)

Adaptive Online Experimental Design for Causal Discovery
par: Elahi, Muhammad Qasim, et autres
Publié: (2024)

Unsupervised Machine Learning for Scientific Discovery: Workflow and Best Practices
par: Chang, Andersen, et autres
Publié: (2025)

SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling
par: Vowels, Matthew J.
Publié: (2023)

DataMap: A Portable Application for Visualizing High-Dimensional Data
par: Ge, Xijin
Publié: (2025)

bioLeak: Leakage-Aware Modeling and Diagnostics for Machine Learning in R
par: Korkmaz, Selçuk
Publié: (2026)

fastml: Guarded Resampling Workflows for Safer Automated Machine Learning in R
par: Korkmaz, Selcuk, et autres
Publié: (2026)

A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems
par: Han, Jessy Xinyi, et autres
Publié: (2024)

High-Dimensional Statistical Process Control via Manifold Fitting and Learning
par: Tas, Burak I., et autres
Publié: (2025)

DeepBridge: A Unified and Production-Ready Framework for Multi-Dimensional Machine Learning Validation
par: Haase, Gustavo Coelho, et autres
Publié: (2025)

Monitoring Machine Learning Forecasts for Platform Data Streams
par: Rombouts, Jeroen, et autres
Publié: (2024)

Causal Machine Learning for Surgical Interventions
par: Tamo, J. Ben, et autres
Publié: (2025)

Learning Causal Response Representations through Direct Effect Analysis
par: Durand, Homer, et autres
Publié: (2025)

Double Machine Learning Methods for Estimating Average Treatment Effects: A Comparative Study
par: Tan, Xiaoqing, et autres
Publié: (2022)

Nonparametric Linear Discriminant Analysis for High Dimensional Matrix-Valued Data
par: Oh, Seungyeon, et autres
Publié: (2025)

BanditCAT and AutoIRT: Machine Learning Approaches to Computerized Adaptive Testing and Item Calibration
par: Sharpnack, James, et autres
Publié: (2024)

Bayesian Causal Forests for Longitudinal Data: Assessing the Impact of Part-Time Work on Growth in High School Mathematics Achievement
par: McJames, Nathan, et autres
Publié: (2024)

Data Curation for Machine Learning Interatomic Potentials by Determinantal Point Processes
par: Zou, Joanna, et autres
Publié: (2026)

A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis
par: Minoccheri, Cristian, et autres
Publié: (2026)

DRtool: An Interactive Tool for Analyzing High-Dimensional Clusterings
par: Lin, Justin, et autres
Publié: (2025)

Exploring Educational Equity: A Machine Learning Approach to Unravel Achievement Disparities in Georgia
par: Ma, Yichen, et autres
Publié: (2024)

Interval Prediction of Annual Average Daily Traffic on Local Roads via Quantile Random Forest with High-Dimensional Spatial Data
par: Yao, Ying, et autres
Publié: (2025)

A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals
par: Su, Yuqi, et autres
Publié: (2024)

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies
par: Gutman, Rom, et autres
Publié: (2025)

Human Limits in Machine Learning: Prediction of Plant Phenotypes Using Soil Microbiome Data
par: Aghdam, Rosa, et autres
Publié: (2023)

Interpretable Machine Learning for Cognitive Aging: Handling Missing Data and Uncovering Social Determinant
par: Mao, Xi, et autres
Publié: (2025)

Fusion Sampling Validation in Data Partitioning for Machine Learning
par: Udomboso, Christopher Godwin, et autres
Publié: (2025)

Age-Dependent Heterogeneity in the Association Between Physical Activity and Mental Distress: A Causal Machine Learning Analysis of 3.2 Million U.S. Adults
par: Shan, Yuan
Publié: (2026)

Establishing Nationwide Power System Vulnerability Index across US Counties Using Interpretable Machine Learning
par: Ma, Junwei, et autres
Publié: (2024)

Parallel Algorithms for Structured Sparse Support Vector Machines: Application in Music Genre Classification
par: Liang, Rongmei, et autres
Publié: (2025)

Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data
par: Hasan, Nazmul, et autres
Publié: (2024)

Mapping Methane -- The Impact of Dairy Farm Practices on Emissions Through Satellite Data and Machine Learning
par: Bi, Hanqing, et autres
Publié: (2024)