Cover Image

Nonparametric learning of heterogeneous graphical model on network-linked data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Yuwen, Liu, Changyu, He, Xin, Wang, Junhui
Format:	Preprint
Published:	2025
Subjects:	Methodology Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Community detection in heterogeneous signed networks
by: Wang, Yuwen, et al.
Published: (2025)

Convex estimation of Gaussian graphical regression models with covariates
by: Liu, Ruobin, et al.
Published: (2024)

Scalable and non-iterative graphical model estimation
by: Khare, Kshitij, et al.
Published: (2024)

Functional effects models: Accounting for preference heterogeneity in panel data with machine learning
by: Salvadé, Nicolas, et al.
Published: (2025)

Nonparametric estimation of time-varying network connections by multi-stage smoothing
by: Lee, Jeonghwan, et al.
Published: (2026)

Modeling massive highly-multivariate nonstationary spatial data with the basis graphical lasso
by: Krock, Mitchell, et al.
Published: (2021)

Adaptive Bayesian Multivariate Spline Knot Inference with Prior Specifications on Model Complexity
by: He, Junhui, et al.
Published: (2024)

Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes
by: Wu, Bohan, et al.
Published: (2024)

Confidence Diagram of Nonparametric Ranking for Uncertainty Assessment in Large Language Models Evaluation
by: Wang, Zebin, et al.
Published: (2024)

SPARKLE: A Nonparametric Approach for Online Decision-Making with High-Dimensional Covariates
by: Wang, Wenjia, et al.
Published: (2025)

Nonparametric efficient inference for network quantile causal effects under partial interference
by: Cheng, Chao, et al.
Published: (2026)

Extremal graphical modeling with latent variables via convex optimization
by: Engelke, Sebastian, et al.
Published: (2024)

Bias-Targeted Nonparametric Balancing for Stable Causal Mediation Analysis
by: Liu, Chang, et al.
Published: (2024)

Targeted learning of heterogeneous treatment effect curves for right censored or left truncated time-to-event data
by: Pryce, Matthew, et al.
Published: (2026)

Nonparametric estimation of conditional probability distributions using a generative approach based on conditional push-forward neural networks
by: Franco, Nicola Rares, et al.
Published: (2025)

Exploration of the search space of Gaussian graphical models for paired data
by: Roverato, Alberto, et al.
Published: (2023)

Nonparametric estimation of Hawkes processes with RKHSs
by: Bonnet, Anna, et al.
Published: (2024)

High-dimensional Nonparametric Contextual Bandit Problem
by: Iwazaki, Shogo, et al.
Published: (2025)

Nonparametric Regression Discontinuity Designs with Survival Outcomes
by: Schuessler, Maximilian, et al.
Published: (2026)

Nonparametric Identification and Inference for Counterfactual Distributions with Confounding
by: Sun, Jianle, et al.
Published: (2026)

Leveraging heterogeneity for identifiability: Bayesian order-based learning of multiple DAGs
by: Chang, Hyunwoong, et al.
Published: (2026)

Transfer Learning for Nonparametric Contextual Dynamic Pricing
by: Wang, Fan, et al.
Published: (2025)

Joint modeling for learning decision-making dynamics in behavioral experiments
by: Bian, Yuan, et al.
Published: (2025)

Locally Private Nonparametric Contextual Multi-armed Bandits
by: Ma, Yuheng, et al.
Published: (2025)

EM Approaches to Nonparametric Estimation for Mixture of Linear Regressions
by: Welbaum, Andrew, et al.
Published: (2025)

Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data
by: Karlsson, Rickard, et al.
Published: (2025)

DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models
by: Blöbaum, Patrick, et al.
Published: (2022)

Interval Estimation of Coefficients in Penalized Regression Models of Insurance Data
by: Manna, Alokesh, et al.
Published: (2024)

Learning Multi-type heterogeneous interacting particle systems
by: Lang, Quanjun, et al.
Published: (2026)

Transfer Learning for Kernel-based Regression
by: Wang, Chao, et al.
Published: (2023)

TRIP: A Nonparametric Test to Diagnose Biased Feature Importance Scores
by: Foote, Aaron, et al.
Published: (2025)

Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
by: Guo, Anna, et al.
Published: (2023)

Wasserstein Distributionally Robust Nonparametric Regression
by: Liu, Changyu, et al.
Published: (2025)

Nonparametric learning of covariate-based Markov jump processes using RKHS techniques
by: Han, Yuchen, et al.
Published: (2025)

Neural networks for geospatial data
by: Zhan, Wentao, et al.
Published: (2023)

Automatic debiasing of neural networks via moment-constrained learning
by: Hines, Christian L., et al.
Published: (2024)

Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
by: Ye, Shengbin, et al.
Published: (2024)

Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach
by: Luo, Jiajun, et al.
Published: (2023)

Optimal Demixing of Nonparametric Densities
by: Fan, Jianqing, et al.
Published: (2026)

Identification of Average Treatment Effects in Nonparametric Panel Models
by: Athey, Susan, et al.
Published: (2025)