A Propagation Framework for Network Regression
Fuente:
arXiv
Saved in:
| Main Authors: | Ma, Yingying, Leng, Chenlei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Regression Analysis of Reciprocity in Directed Networks
by: Feng, Rui, et al.
Published: (2025)
by: Feng, Rui, et al.
Published: (2025)
A Sparse Beta Regression Model for Network Analysis
by: Stein, Stefan, et al.
Published: (2020)
by: Stein, Stefan, et al.
Published: (2020)
Modelling Directed Networks with Reciprocity
by: Feng, Rui, et al.
Published: (2024)
by: Feng, Rui, et al.
Published: (2024)
Causal Inference under Interference: Regression Adjustment and Optimality
by: Fan, Xinyuan, et al.
Published: (2025)
by: Fan, Xinyuan, et al.
Published: (2025)
Residual Importance Weighted Transfer Learning For High-dimensional Linear Regression
by: Zhao, Junlong, et al.
Published: (2023)
by: Zhao, Junlong, et al.
Published: (2023)
Generalized Correlation Regression for Disentangling Dependence in Clustered Data
by: Wang, Yibo, et al.
Published: (2025)
by: Wang, Yibo, et al.
Published: (2025)
Low-Rank Graphon Learning for Networks
by: Fan, Xinyuan, et al.
Published: (2025)
by: Fan, Xinyuan, et al.
Published: (2025)
Supervised centrality via sparse network influence regression: an application to the 2021 Henan floods' social network
by: Ma, Yingying, et al.
Published: (2024)
by: Ma, Yingying, et al.
Published: (2024)
Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures
by: Leng, Chenlei, et al.
Published: (2024)
by: Leng, Chenlei, et al.
Published: (2024)
Regression adjustment in covariate-adaptive randomized experiments with missing covariates
by: Fu, Wanjia, et al.
Published: (2025)
by: Fu, Wanjia, et al.
Published: (2025)
Scalable Expectation Propagation for Mixed-Effects Regression
by: Zhou, Jackson, et al.
Published: (2024)
by: Zhou, Jackson, 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)
A two-way heterogeneity model for dynamic networks
by: Jiang, Binyan, et al.
Published: (2023)
by: Jiang, Binyan, et al.
Published: (2023)
Linear Discriminant Analysis with High-dimensional Mixed Variables
by: Jiang, Binyan, et al.
Published: (2021)
by: Jiang, Binyan, et al.
Published: (2021)
A Generalized Estimating Equation Approach to Network Regression
by: Ghosh, Riddhi Pratim, et al.
Published: (2023)
by: Ghosh, Riddhi Pratim, et al.
Published: (2023)
Unified Operator Framework for Functional and Multivariate Regression
by: Carpenter, Mark, et al.
Published: (2026)
by: Carpenter, Mark, et al.
Published: (2026)
Balancing Covariates in Survey Experiments
by: Tian, Pengfei, et al.
Published: (2026)
by: Tian, Pengfei, et al.
Published: (2026)
Treatment effect estimation under covariate-adaptive randomization with heavy-tailed outcomes
by: Li, Hongzi, et al.
Published: (2024)
by: Li, Hongzi, et al.
Published: (2024)
Weighted Regression with Sybil Networks
by: Shah, Nihar
Published: (2024)
by: Shah, Nihar
Published: (2024)
Propensity Score Propagation: A General Framework for Design-Based Inference with Unknown Propensity Scores
by: Heng, Siyu, et al.
Published: (2026)
by: Heng, Siyu, et al.
Published: (2026)
Bias Correction for Semiparametric Regression Models
by: Zhang, Yuming, et al.
Published: (2026)
by: Zhang, Yuming, et al.
Published: (2026)
Training of Spiking Neural Networks with Expectation-Propagation
by: Yao, Dan, et al.
Published: (2025)
by: Yao, Dan, et al.
Published: (2025)
Multilayer Network Regression with Eigenvector Centrality and Community Structure
by: Han, Zhuoye, et al.
Published: (2023)
by: Han, Zhuoye, et al.
Published: (2023)
Network-aware IV Regression for Causal Node Discovery and Estimation
by: Pal, Samhita, et al.
Published: (2026)
by: Pal, Samhita, et al.
Published: (2026)
Generalized Geographically Weighted Regression Model within a Modularized Bayesian Framework
by: Liu, Yang, et al.
Published: (2021)
by: Liu, Yang, et al.
Published: (2021)
Fair Regression under Demographic Parity: A Unified Framework
by: Feng, Yongzhen, et al.
Published: (2026)
by: Feng, Yongzhen, et al.
Published: (2026)
Bagged Polynomial Regression and Neural Networks
by: Klosin, Sylvia, et al.
Published: (2022)
by: Klosin, Sylvia, et al.
Published: (2022)
Unified Framework for Hybrid Aleatory and Epistemic Uncertainty Propagation via Decoupled Multi-Probability Density Evolution Method
by: Luo, Yi, et al.
Published: (2025)
by: Luo, Yi, et al.
Published: (2025)
A Framework of Zero-Inflated Bayesian Negative Binomial Regression Models For Spatiotemporal Data
by: He, Qing, et al.
Published: (2024)
by: He, Qing, et al.
Published: (2024)
A Unified Bayesian Nonparametric Framework for Ordinal, Survival, and Density Regression Using the Complementary Log-Log Link
by: Alam, Entejar, et al.
Published: (2025)
by: Alam, Entejar, et al.
Published: (2025)
HNCI: High-Dimensional Network Causal Inference
by: Du, Wenqin, et al.
Published: (2024)
by: Du, Wenqin, et al.
Published: (2024)
Covariance-Driven Regression Trees: Reducing Overfitting in CART
by: Zhang, Likun, et al.
Published: (2026)
by: Zhang, Likun, et al.
Published: (2026)
Just Ramp-up: Unleash the Potential of Regression-based Estimator for A/B Tests under Network Interference
by: Chen, Qianyi, et al.
Published: (2024)
by: Chen, Qianyi, et al.
Published: (2024)
A Type of Nonlinear Fréchet Regressions
by: Lin, Lu, et al.
Published: (2024)
by: Lin, Lu, et al.
Published: (2024)
Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
by: Deng, Jingwen, et al.
Published: (2026)
by: Deng, Jingwen, et al.
Published: (2026)
A New Framework for Bayesian Function Registration
by: Ma, Yijia, et al.
Published: (2024)
by: Ma, Yijia, et al.
Published: (2024)
High Dimensional Logistic Regression Under Network Dependence
by: Mukherjee, Somabha, et al.
Published: (2021)
by: Mukherjee, Somabha, et al.
Published: (2021)
Local Bayesian Regression
by: Hjort, Nils Lid
Published: (2026)
by: Hjort, Nils Lid
Published: (2026)
Inference for Fréchet Regression
by: Song, Wookyeong, et al.
Published: (2026)
by: Song, Wookyeong, et al.
Published: (2026)
Generalized Rank Regression
by: Tu, Jiyuan, et al.
Published: (2026)
by: Tu, Jiyuan, et al.
Published: (2026)
Similar Items
-
Regression Analysis of Reciprocity in Directed Networks
by: Feng, Rui, et al.
Published: (2025) -
A Sparse Beta Regression Model for Network Analysis
by: Stein, Stefan, et al.
Published: (2020) -
Modelling Directed Networks with Reciprocity
by: Feng, Rui, et al.
Published: (2024) -
Causal Inference under Interference: Regression Adjustment and Optimality
by: Fan, Xinyuan, et al.
Published: (2025) -
Residual Importance Weighted Transfer Learning For High-dimensional Linear Regression
by: Zhao, Junlong, et al.
Published: (2023)