Deep Neural Networks Guided Ensemble Learning for Point Estimation
Fuente:
arXiv
Saved in:
| Main Authors: | Zhan, Tianyu, Fu, Haoda, Kang, Jian |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A general, flexible and harmonious framework to construct interpretable functions in regression analysis
by: Zhan, Tianyu, et al.
Published: (2025)
by: Zhan, Tianyu, et al.
Published: (2025)
Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls
by: Liu, Mochuan, et al.
Published: (2022)
by: Liu, Mochuan, et al.
Published: (2022)
An Integrated and Coherent Framework for Point Estimation and Hypothesis Testing with Concurrent Controls in Platform Trials
by: Zhan, Tianyu, et al.
Published: (2025)
by: Zhan, Tianyu, et al.
Published: (2025)
Integrating RCTs, RWD, AI/ML and Statistics: Next-Generation Evidence Synthesis
by: Yang, Shu, et al.
Published: (2025)
by: Yang, Shu, et al.
Published: (2025)
Unobserved Heterogeneity in Threshold Regression Based on the Hitting Times of a Reflected Brownian Motion for Recurrent Hypoglycemia
by: Xie, Yingfa, et al.
Published: (2026)
by: Xie, Yingfa, et al.
Published: (2026)
Multi-Label Residual Weighted Learning for Individualized Combination Treatment Rule
by: Xu, Qi, et al.
Published: (2023)
by: Xu, Qi, et al.
Published: (2023)
Recurrent Events Modeling Based on a Reflected Brownian Motion with Application to Hypoglycemia
by: Xie, Yingfa, et al.
Published: (2024)
by: Xie, Yingfa, et al.
Published: (2024)
A Class of Computational Methods to Reduce Selection Bias when Designing Phase 3 Clinical Trials
by: Zhan, Tianyu
Published: (2023)
by: Zhan, Tianyu
Published: (2023)
Weighted Average Ensemble for Cholesky-based Covariance Matrix Estimation
by: Kang, Xiaoning, et al.
Published: (2025)
by: Kang, Xiaoning, et al.
Published: (2025)
Semiparametric Weighted Spline Regression (SWSR) in Confirmatory Clinical Trials with Time-Varying Placebo Effects
by: Zhan, Tianyu, et al.
Published: (2025)
by: Zhan, Tianyu, et al.
Published: (2025)
Robust Estimation for Dependent Binary Network Data
by: Liu, Tianyu, et al.
Published: (2025)
by: Liu, Tianyu, et al.
Published: (2025)
Estimating Treatment Effects under Algorithmic Interference: A Structured Neural Networks Approach
by: Zhan, Ruohan, et al.
Published: (2024)
by: Zhan, Ruohan, et al.
Published: (2024)
Bayesian Image-on-Image Regression via Deep Kernel Learning based Gaussian Processes
by: Ma, Guoxuan, et al.
Published: (2023)
by: Ma, Guoxuan, et al.
Published: (2023)
Spatial Deep Convolutional Neural Networks
by: Wang, Qi, et al.
Published: (2024)
by: Wang, Qi, et al.
Published: (2024)
Adaptive Physics-Guided Neural Network
by: Shulman, David, et al.
Published: (2024)
by: Shulman, David, et al.
Published: (2024)
Interpretable Deep Neural Network for Modeling Functional Surrogates
by: Jeon, Yeseul, et al.
Published: (2025)
by: Jeon, Yeseul, et al.
Published: (2025)
Neural Networks for Parameter Estimation of the Discretely Observed Hawkes Process
by: Lambe, Jason J., et al.
Published: (2025)
by: Lambe, Jason J., et al.
Published: (2025)
Neural Networks for Parameter Estimation in Geometrically Anisotropic Geostatistical Models
by: Villazón, Alejandro, et al.
Published: (2024)
by: Villazón, Alejandro, et al.
Published: (2024)
Neural Network Machine Regression (NNMR): A Deep Learning Framework for Uncovering High-order Synergistic Effects
by: Zhang, Jiuchen, et al.
Published: (2026)
by: Zhang, Jiuchen, et al.
Published: (2026)
Causal Estimation of Exposure Shifts with Neural Networks
by: Tec, Mauricio, et al.
Published: (2023)
by: Tec, Mauricio, et al.
Published: (2023)
Amortized Phylodynamic Inference with Neural Bayes Estimators and Recursive Neural Networks
by: Zarebski, Alexander E., et al.
Published: (2026)
by: Zarebski, Alexander E., et al.
Published: (2026)
Estimating heterogeneous treatment effects with survival outcomes via a deep survival learner
by: Sun, Yuming, et al.
Published: (2026)
by: Sun, Yuming, et al.
Published: (2026)
Semiparametric Spatial Point Processes
by: Lin, Xindi, et al.
Published: (2024)
by: Lin, Xindi, et al.
Published: (2024)
Robust CATE Estimation Using Novel Ensemble Methods
by: Machluf, Oshri, et al.
Published: (2024)
by: Machluf, Oshri, et al.
Published: (2024)
Online Estimation with Rolling Validation: Adaptive Nonparametric Estimation with Streaming Data
by: Zhang, Tianyu, et al.
Published: (2023)
by: Zhang, Tianyu, et al.
Published: (2023)
Estimate Time-Varying Exposure Effects via Ensemble Learning-based Marginal Structural Model with Application to Adolescent Cognitive Development Study
by: Zhao, Zhiwei, et al.
Published: (2025)
by: Zhao, Zhiwei, et al.
Published: (2025)
Semiparametric Estimation of the Shape of the Limiting Bivariate Point Cloud
by: Majumder, Reetam, et al.
Published: (2023)
by: Majumder, Reetam, et al.
Published: (2023)
Regularised Spectral Estimation for High-Dimensional Point Processes
by: Pinkney, Carla, et al.
Published: (2024)
by: Pinkney, Carla, et al.
Published: (2024)
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
by: Sainsbury-Dale, Matthew, et al.
Published: (2023)
by: Sainsbury-Dale, Matthew, et al.
Published: (2023)
Super Ensemble Learning Using the Highly-Adaptive-Lasso
by: Wang, Zeyi, et al.
Published: (2023)
by: Wang, Zeyi, et al.
Published: (2023)
DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
by: Kim, Kyum, et al.
Published: (2025)
by: Kim, Kyum, et al.
Published: (2025)
DeepSuM: Deep Sufficient Modality Learning Framework
by: Gao, Zhe, et al.
Published: (2025)
by: Gao, Zhe, et al.
Published: (2025)
HEDE: Heritability estimation in high dimensions by Ensembling Debiased Estimators
by: Song, Yanke, et al.
Published: (2024)
by: Song, Yanke, et al.
Published: (2024)
Uncertainty-Aware Ideal Point Estimation via Variational EM
by: Seo, Kwangok, et al.
Published: (2026)
by: Seo, Kwangok, et al.
Published: (2026)
Two-stage Estimators for Spatial Confounding with Point-Referenced Data
by: Wiecha, Nate, et al.
Published: (2024)
by: Wiecha, Nate, et al.
Published: (2024)
Automatic Change-Point Detection in Time Series via Deep Learning
by: Li, Jie, et al.
Published: (2022)
by: Li, Jie, et al.
Published: (2022)
Neural networks for geospatial data
by: Zhan, Wentao, et al.
Published: (2023)
by: Zhan, Wentao, et al.
Published: (2023)
Minimal Sufficient Representations for Self-interpretable Deep Neural Networks
by: Tan, Zhiyao, et al.
Published: (2026)
by: Tan, Zhiyao, et al.
Published: (2026)
Estimation of treatment effect in clinical trials of continuous endpoints with retrieved dropouts
by: Kang, Myeongjong, et al.
Published: (2026)
by: Kang, Myeongjong, et al.
Published: (2026)
Neural Posterior Estimation for Stochastic Epidemic Modeling
by: Chatha, Prayag, et al.
Published: (2024)
by: Chatha, Prayag, et al.
Published: (2024)
Similar Items
-
A general, flexible and harmonious framework to construct interpretable functions in regression analysis
by: Zhan, Tianyu, et al.
Published: (2025) -
Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls
by: Liu, Mochuan, et al.
Published: (2022) -
An Integrated and Coherent Framework for Point Estimation and Hypothesis Testing with Concurrent Controls in Platform Trials
by: Zhan, Tianyu, et al.
Published: (2025) -
Integrating RCTs, RWD, AI/ML and Statistics: Next-Generation Evidence Synthesis
by: Yang, Shu, et al.
Published: (2025) -
Unobserved Heterogeneity in Threshold Regression Based on the Hitting Times of a Reflected Brownian Motion for Recurrent Hypoglycemia
by: Xie, Yingfa, et al.
Published: (2026)