Causality-Encoded Diffusion Models for Interventional Sampling and Edge Inference
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Li, Shen, Xiaotong, Pan, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Diffusion-Driven High-Dimensional Variable Selection
by: Wang, Minjie, et al.
Published: (2025)
by: Wang, Minjie, et al.
Published: (2025)
Modeling Causal Mechanisms with Diffusion Models for Interventional and Counterfactual Queries
by: Chao, Patrick, et al.
Published: (2023)
by: Chao, Patrick, et al.
Published: (2023)
Enhancing Causal Effect Estimation with Diffusion-Generated Data
by: Chen, Li, et al.
Published: (2025)
by: Chen, Li, et al.
Published: (2025)
Interventional Time Series Priors for Causal Foundation Models
by: Thumm, Dennis, et al.
Published: (2026)
by: Thumm, Dennis, et al.
Published: (2026)
Linking Model Intervention to Causal Interpretation in Model Explanation
by: Cheng, Debo, et al.
Published: (2024)
by: Cheng, Debo, et al.
Published: (2024)
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
by: Agarwal, Abhineet, et al.
Published: (2023)
by: Agarwal, Abhineet, et al.
Published: (2023)
Sample Efficient Bayesian Learning of Causal Graphs from Interventions
by: Zhou, Zihan, et al.
Published: (2024)
by: Zhou, Zihan, et al.
Published: (2024)
Probabilistic Modelling is Sufficient for Causal Inference
by: Mlodozeniec, Bruno, et al.
Published: (2025)
by: Mlodozeniec, Bruno, et al.
Published: (2025)
Conditional Data Synthesis Augmentation
by: Tian, Xinyu, et al.
Published: (2025)
by: Tian, Xinyu, et al.
Published: (2025)
Interventional Processes for Causal Uncertainty Quantification
by: Dance, Hugh, et al.
Published: (2024)
by: Dance, Hugh, et al.
Published: (2024)
Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priors
by: Dhawan, Nikita, et al.
Published: (2026)
by: Dhawan, Nikita, et al.
Published: (2026)
RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model
by: Li, Peiwen, et al.
Published: (2024)
by: Li, Peiwen, et al.
Published: (2024)
Feature Matching Intervention: Leveraging Observational Data for Causal Representation Learning
by: Li, Haoze, et al.
Published: (2025)
by: Li, Haoze, et al.
Published: (2025)
Causal Interventional Prediction System for Robust and Explainable Effect Forecasting
by: Chu, Zhixuan, et al.
Published: (2024)
by: Chu, Zhixuan, et al.
Published: (2024)
Causal Inference with the "Napkin Graph"
by: Guo, Anna, et al.
Published: (2025)
by: Guo, Anna, et al.
Published: (2025)
Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data
by: Luo, Gongxu, et al.
Published: (2025)
by: Luo, Gongxu, et al.
Published: (2025)
Causal Inference with Complex Treatments: A Survey
by: Wang, Yingrong, et al.
Published: (2024)
by: Wang, Yingrong, et al.
Published: (2024)
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
by: Zhu, Yaochen, et al.
Published: (2024)
by: Zhu, Yaochen, et al.
Published: (2024)
Controllable Generative Sandbox for Causal Inference
by: Zhang, Qi, et al.
Published: (2026)
by: Zhang, Qi, et al.
Published: (2026)
A Semiparametric Approach to Causal Inference
by: Zhang, Archer Gong, et al.
Published: (2024)
by: Zhang, Archer Gong, et al.
Published: (2024)
Valid Inference After Causal Discovery
by: Gradu, Paula, et al.
Published: (2022)
by: Gradu, Paula, et al.
Published: (2022)
Interventional Causal Discovery in a Mixture of DAGs
by: Varıcı, Burak, et al.
Published: (2024)
by: Varıcı, Burak, et al.
Published: (2024)
Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
by: Guo, Anna, et al.
Published: (2023)
by: Guo, Anna, et al.
Published: (2023)
Nonlinear Causal Discovery with Confounders
by: Li, Chunlin, et al.
Published: (2023)
by: Li, Chunlin, et al.
Published: (2023)
CaMU: Disentangling Causal Effects in Deep Model Unlearning
by: Shen, Shaofei, et al.
Published: (2024)
by: Shen, Shaofei, et al.
Published: (2024)
Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)
by: Abadie, Alberto, et al.
Published: (2024)
New User Event Prediction Through the Lens of Causal Inference
by: Yuchi, Henry Shaowu, et al.
Published: (2024)
by: Yuchi, Henry Shaowu, et al.
Published: (2024)
HNCI: High-Dimensional Network Causal Inference
by: Du, Wenqin, et al.
Published: (2024)
by: Du, Wenqin, et al.
Published: (2024)
Bayesian Causal Inference with Gaussian Process Networks
by: Giudice, Enrico, et al.
Published: (2024)
by: Giudice, Enrico, et al.
Published: (2024)
An Overview of Causal Inference using Kernel Embeddings
by: Sejdinovic, Dino
Published: (2024)
by: Sejdinovic, Dino
Published: (2024)
Predictive Causal Inference via Spatio-Temporal Modeling and Penalized Empirical Likelihood
by: Lee, Byunghee, et al.
Published: (2025)
by: Lee, Byunghee, et al.
Published: (2025)
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
by: Komanduri, Aneesh, et al.
Published: (2024)
by: Komanduri, Aneesh, et al.
Published: (2024)
Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)
by: Arbour, David, et al.
Published: (2025)
Testing Generalizability in Causal Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)
by: Manela, Daniel de Vassimon, et al.
Published: (2024)
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
by: Dhir, Anish, et al.
Published: (2025)
by: Dhir, Anish, et al.
Published: (2025)
Towards Causal Foundation Model: on Duality between Causal Inference and Attention
by: Zhang, Jiaqi, et al.
Published: (2023)
by: Zhang, Jiaqi, et al.
Published: (2023)
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
by: Gamella, Juan L., et al.
Published: (2022)
by: Gamella, Juan L., et al.
Published: (2022)
A Frequentist Statistical Introduction to Variational Inference, Autoencoders, and Diffusion Models
by: Chen, Yen-Chi
Published: (2025)
by: Chen, Yen-Chi
Published: (2025)
Causal Inference on Stopped Random Walks in Online Advertising
by: Yu, Jia Yuan
Published: (2026)
by: Yu, Jia Yuan
Published: (2026)
Causal Inference for Preprocessed Outcomes with an Application to Functional Connectivity
by: Wang, Zihang, et al.
Published: (2026)
by: Wang, Zihang, et al.
Published: (2026)
Similar Items
-
Diffusion-Driven High-Dimensional Variable Selection
by: Wang, Minjie, et al.
Published: (2025) -
Modeling Causal Mechanisms with Diffusion Models for Interventional and Counterfactual Queries
by: Chao, Patrick, et al.
Published: (2023) -
Enhancing Causal Effect Estimation with Diffusion-Generated Data
by: Chen, Li, et al.
Published: (2025) -
Interventional Time Series Priors for Causal Foundation Models
by: Thumm, Dennis, et al.
Published: (2026) -
Linking Model Intervention to Causal Interpretation in Model Explanation
by: Cheng, Debo, et al.
Published: (2024)