Cover Image

s-ID: Causal Effect Identification in a Sub-Population

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Abouei, Amir Mohammad, Mokhtarian, Ehsan, Kiyavash, Negar
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Causal Effect Identification in a Sub-Population with Latent Variables
by: Abouei, Amir Mohammad, et al.
Published: (2024)

QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
by: Shahverdikondori, Mohammad, et al.
Published: (2024)

Fast Proxy Experiment Design for Causal Effect Identification
by: Elahi, Sepehr, et al.
Published: (2024)

Multi-Domain Causal Discovery in Bijective Causal Models
by: Jalaldoust, Kasra, et al.
Published: (2025)

Causal Effect Identification in LiNGAM Models with Latent Confounders
by: Tramontano, Daniele, et al.
Published: (2024)

Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
by: Tramontano, Daniele, et al.
Published: (2025)

Recursive Causal Discovery
by: Mokhtarian, Ehsan, et al.
Published: (2024)

Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
by: Kivva, Yaroslav, et al.
Published: (2025)

Near-Optimal Experiment Design in Linear non-Gaussian Cyclic Models
by: Sharifian, Ehsan, et al.
Published: (2025)

Towards a holistic understanding of Selection Bias for Causal Effect Identification
by: Qiu, Yiwen, et al.
Published: (2026)

Causal Identification in Time Series Models
by: Jahn, Erik, et al.
Published: (2025)

Pure Exploration Beyond Reward Feedback: The Role of Post-Action Context
by: Shahverdikondori, Mohammad, et al.
Published: (2025)

Causal Discovery in Linear Models with Unobserved Variables and Measurement Error
by: Yang, Yuqin, et al.
Published: (2024)

On the Granularity of Causal Effect Identifiability
by: Chen, Yizuo, et al.
Published: (2025)

Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data
by: Yang, Yuqin, et al.
Published: (2023)

Identifying Conditional Causal Effects in MPDAGs
by: LaPlante, Sara, et al.
Published: (2025)

Transferring Causal Effects using Proxies
by: Iglesias-Alonso, Manuel, et al.
Published: (2025)

Compositional Models for Estimating Causal Effects
by: Pruthi, Purva, et al.
Published: (2024)

Conformal Prediction for Causal Effects of Continuous Treatments
by: Schröder, Maresa, et al.
Published: (2024)

Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning
by: Meherab, Md Muntaqim, et al.
Published: (2026)

The Estimation of Continual Causal Effect for Dataset Shifting Streams
by: Chen, Baining, et al.
Published: (2025)

NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation
by: Reddy, Abbavaram Gowtham, et al.
Published: (2022)

Towards Learning and Explaining Indirect Causal Effects in Neural Networks
by: Reddy, Abbavaram Gowtham, et al.
Published: (2023)

A Recipe for Causal Graph Regression: Confounding Effects Revisited
by: Yin, Yujia, et al.
Published: (2025)

Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
by: Mahajan, Divyat, et al.
Published: (2022)

Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
by: Rahman, Md Musfiqur, et al.
Published: (2024)

Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)

Towards Causal Foundation Model: on Duality between Causal Inference and Attention
by: Zhang, Jiaqi, et al.
Published: (2023)

Language Agents Meet Causality -- Bridging LLMs and Causal World Models
by: Gkountouras, John, et al.
Published: (2024)

Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
by: Ng, Woon Yee, et al.
Published: (2025)

Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-offs: A Causal Inference Approach
by: Liu, Xiaohui, et al.
Published: (2022)

Interventional Causal Discovery in a Mixture of DAGs
by: Varıcı, Burak, et al.
Published: (2024)

Causal Preference Elicitation
by: Bonilla, Edwin V., et al.
Published: (2026)

CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2026)

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
by: Takayama, Masayuki, et al.
Published: (2024)

ALCM: Autonomous LLM-Augmented Causal Discovery Framework
by: Khatibi, Elahe, et al.
Published: (2024)

Black Box Causal Inference: Effect Estimation via Meta Prediction
by: Bynum, Lucius E. J., et al.
Published: (2025)

Causal Temporal Regime Structure Learning
by: Rahmani, Abdellah, et al.
Published: (2023)

Marginal Causal Flows for Validation and Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)

Causal Layering via Conditional Entropy
by: Feigenbaum, Itai, et al.
Published: (2024)