Cover Image

On Efficient Adjustment for Micro Causal Effects in Summary Causal Graphs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Belciug, Isabela, Ferreira, Simon, Assaad, Charles K.
Format:	Preprint
Published:	2025
Subjects:	Methodology Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs
by: Ferreira, Simon, et al.
Published: (2024)

Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding
by: Ferreira, Simon, et al.
Published: (2024)

Orientability of Causal Relations in Time Series using Summary Causal Graphs and Faithful Distributions
by: Loranchet, Timothée, et al.
Published: (2025)

Identifying Macro Causal Effects in C-DMGs over DMGs
by: Ferreira, Simon, et al.
Published: (2025)

Causal reasoning in difference graphs
by: Assaad, Charles K.
Published: (2024)

Identifiability of Direct Effects from Summary Causal Graphs
by: Ferreira, Simon, et al.
Published: (2023)

Towards identifiability of micro total effects in summary causal graphs with latent confounding: extension of the front-door criterion
by: Assaad, Charles K.
Published: (2024)

Identifying Macro Causal Effects in a C-DMG over ADMGs
by: Ferreira, Simon, et al.
Published: (2025)

Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs
by: Wienöbst, Marcel, et al.
Published: (2022)

Moments of Causal Effects
by: Kawakami, Yuta, et al.
Published: (2025)

Constrained Identifiability of Causal Effects
by: Chen, Yizuo, et al.
Published: (2024)

Retrieving Classes of Causal Orders with Inconsistent Knowledge Bases
by: Baldo, Federico, et al.
Published: (2024)

Bounding Causal Effects with Leaky Instruments
by: Watson, David S., et al.
Published: (2024)

Efficient Causal Graph Discovery Using Large Language Models
by: Jiralerspong, Thomas, et al.
Published: (2024)

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

A Topological Sorting Criterion for Random Causal Directed Acyclic Graphs
by: Reisach, Alexander G., et al.
Published: (2026)

Practically Effective Adjustment Variable Selection in Causal Inference
by: Noda, Atsushi, et al.
Published: (2025)

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

Robust Weighted Triangulation of Causal Effects Under Model Uncertainty
by: Bhattacharya, Rohit, et al.
Published: (2026)

Beyond Means: Topological Causal Effects under Persistent-Homology Ignorability
by: Saki, Amir, et al.
Published: (2026)

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)

Multiple Treatments Causal Effects Estimation with Task Embeddings and Balanced Representation Learning
by: Murakami, Yuki, et al.
Published: (2025)

CausalGuard: Conformal Inference under Graph Uncertainty
by: Singh, Vikash, et al.
Published: (2026)

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

Causal Inference under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects
by: Kubota, Kohsuke, et al.
Published: (2025)

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

Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, 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)

s-ID: Causal Effect Identification in a Sub-Population
by: Abouei, Amir Mohammad, et al.
Published: (2023)

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

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

Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects
by: Loranchet, Timothée, et al.
Published: (2025)

When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
by: Jiang, Wenzhao, et al.
Published: (2023)

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

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

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

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