Image de couverture de livre

Stochastic Neural Networks for Causal Inference with Missing Confounders

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Fang, Yaxin, Liang, Faming
Format:	Preprint
Publié:	2026
Sujets:	Computation
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Causal-StoNet: Causal Inference for High-Dimensional Complex Data
par: Fang, Yaxin, et autres
Publié: (2024)

Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks
par: Kim, Sehwan, et autres
Publié: (2025)

Graph Neural Networks for Causal Inference Under Network Confounding
par: Leung, Michael P., et autres
Publié: (2022)

Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
par: Shih, Frank, et autres
Publié: (2025)

Comparing Causal Inference Methods for Point Exposures with Missing Confounders: A Simulation Study
par: Benz, Luke, et autres
Publié: (2024)

Harmonizing knowledge Transfer in Neural Network with Unified Distillation
par: Huang, Yaomin, et autres
Publié: (2024)

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
par: Schröder, Maresa, et autres
Publié: (2023)

Efficient Nonparametric Inference for Mediation Analysis with Nonignorable Missing Confounders
par: Shan, Jiawei, et autres
Publié: (2024)

Causal Discovery under Latent Class Confounding
par: Mazaheri, Bijan, et autres
Publié: (2023)

Causal Fine-Tuning under Latent Confounded Shift
par: Yu, Jialin, et autres
Publié: (2024)

Causal Inference with Missing Exposures and Missing Outcomes
par: Landsiedel, Kirsten E., et autres
Publié: (2025)

GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding
par: Oprescu, Miruna, et autres
Publié: (2025)

Causal Inference With Observational Data and Unobserved Confounding Variables
par: Jarrett E. K. Byrnes, et autres
Publié: (2025)

Extended Fiducial Inference: Toward an Automated Process of Statistical Inference
par: Liang, Faming, et autres
Publié: (2024)

Causal Inference with Categorical Unobserved Confounder via Mixture Learning
par: Saha, Aytijhya, et autres
Publié: (2026)

Multimodal Guidance Network for Missing-Modality Inference in Content Moderation
par: Zhao, Zhuokai, et autres
Publié: (2023)

Compositional Inference for Bayesian Networks and Causality
par: Jacobs, Bart, et autres
Publié: (2025)

CausalMamba: Scalable Conditional State Space Models for Neural Causal Inference
par: Bae, Sangyoon, et autres
Publié: (2025)

Supporting Vision-Language Model Inference with Confounder-pruning Knowledge Prompt
par: Li, Jiangmeng, et autres
Publié: (2022)

When Is Causal Inference Possible? A Statistical Test for Unmeasured Confounding
par: Liu, Muye, et autres
Publié: (2025)

Long-term Causal Inference via Modeling Sequential Latent Confounding
par: Chen, Weilin, et autres
Publié: (2025)

Uncertainty Quantification for Large-Scale Deep Networks via Post-StoNet Modeling
par: Sun, Yan, et autres
Publié: (2025)

Research on Deep Learning Model of Feature Extraction Based on Convolutional Neural Network
par: Liu, Houze, et autres
Publié: (2024)

MuPlon: Multi-Path Causal Optimization for Claim Verification through Controlling Confounding
par: Guo, Hanghui, et autres
Publié: (2025)

Double Robust Weighted Regression with Missing Confounders
par: Bagmar, Md. Shaddam Hossain, et autres
Publié: (2026)

Disparate Effect Of Missing Mediators On Transportability of Causal Effects
par: Mhasawade, Vishwali, et autres
Publié: (2024)

The Missing Link: Allocation Performance in Causal Machine Learning
par: Fischer-Abaigar, Unai, et autres
Publié: (2024)

Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and Reconstruction
par: Lei, Pengcheng, et autres
Publié: (2023)

LLM-based Agents for Automated Confounder Discovery and Subgroup Analysis in Causal Inference
par: Lee, Po-Han, et autres
Publié: (2025)

Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
par: Zheng, Jiajing, et autres
Publié: (2021)

Long-term Causal Inference Under Persistent Confounding via Data Combination
par: Imbens, Guido, et autres
Publié: (2022)

Confounded Budgeted Causal Bandits
par: Jamshidi, Fateme, et autres
Publié: (2024)

Nonlinear Causal Discovery with Confounders
par: Li, Chunlin, et autres
Publié: (2023)

Preconditioners for the Stochastic Training of Neural Fields
par: Chng, Shin-Fang, et autres
Publié: (2024)

Causal Inference on Missing Exposure via Robust Estimation
par: Shi, Yuliang, et autres
Publié: (2024)

Causal Inference with Outcomes Truncated by Death and Missing Not at Random
par: Li, Wei, et autres
Publié: (2024)

Causal Inference With Outcomes Truncated by Death and Missing Not at Random
par: Wei Li, et autres
Publié: (2025)

Modelling the Human Intuition to Complete the Missing Information in Images for Convolutional Neural Networks
par: Koç, Robin, et autres
Publié: (2024)

Missed Causes and Ambiguous Effects: Counterfactuals Pose Challenges for Interpreting Neural Networks
par: Mueller, Aaron
Publié: (2024)

Federated Learning on Stochastic Neural Networks
par: Tang, Jingqiao, et autres
Publié: (2025)