Image de couverture de livre

Canonical Representations of Markovian Structural Causal Models: A Framework for Counterfactual Reasoning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	de Lara, Lucas
Format:	Preprint
Publié:	2025
Sujets:	Artificial Intelligence Statistics Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Counterfactual Generative Modeling with Variational Causal Inference
par: Wu, Yulun, et autres
Publié: (2024)

Distribution-consistency Structural Causal Models
par: Gong, Heyang, et autres
Publié: (2024)

Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models
par: Rajendran, Goutham, et autres
Publié: (2024)

A General Framework on Conditions for Constraint-based Causal Learning
par: Teh, Kai Z., et autres
Publié: (2024)

Foundations of Structural Causal Models with Latent Selection
par: Chen, Leihao, et autres
Publié: (2024)

A Measure-Theoretic Axiomatisation of Causality
par: Park, Junhyung, et autres
Publié: (2023)

Conditional Performance Guarantee for Large Reasoning Models
par: Huang, Jianguo, et autres
Publié: (2026)

Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning
par: Yu, Xiangning, et autres
Publié: (2025)

Cyclic Counterfactuals under Shift-Scale Interventions
par: Saha, Saptarshi, et autres
Publié: (2025)

Complete Characterization for Adjustment in Summary Causal Graphs of Time Series
par: Yvernes, Clément, et autres
Publié: (2025)

Causal Digital Twins for Cyber-Physical Security: A Framework for Robust Anomaly Detection in Industrial Control Systems
par: Homaei, Mohammadhossein, et autres
Publié: (2025)

Counterfactual reasoning: an analysis of in-context emergence
par: Miller, Moritz, et autres
Publié: (2025)

The Logic of Counterfactuals and the Epistemology of Causal Inference
par: Lin, Hanti
Publié: (2024)

On the Provable Performance Guarantee of Efficient Reasoning Models
par: Zeng, Hao, et autres
Publié: (2025)

A Computational Theory for Efficient Mini Agent Evaluation with Causal Guarantees
par: Yan, Hedong
Publié: (2025)

Variational Causal Inference
par: Wu, Yulun, et autres
Publié: (2022)

The Geometry of Knowing: From Possibilistic Ignorance to Probabilistic Certainty -- A Measure-Theoretic Framework for Epistemic Convergence
par: Jah, Moriba Kemessia
Publié: (2026)

A Graphical Global Optimization Framework for Parameter Estimation of Statistical Models with Nonconvex Regularization Functions
par: Davarnia, Danial, et autres
Publié: (2025)

Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
par: Li, Gen, et autres
Publié: (2024)

Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation
par: Khellaf, Rémi, et autres
Publié: (2025)

BBScoreV2: Learning Time-Evolution and Latent Alignment from Stochastic Representation
par: Zhang, Tianhao, et autres
Publié: (2024)

Representation learning with a transformer by contrastive learning for money laundering detection
par: Guéneau, Harold, et autres
Publié: (2025)

Reject, Resample, Repeat: Understanding Parallel Reasoning in Language Model Inference
par: Golowich, Noah, et autres
Publié: (2026)

Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods
par: Shen, Zhaiming, et autres
Publié: (2025)

Don't Pass@k: A Bayesian Framework for Large Language Model Evaluation
par: Hariri, Mohsen, et autres
Publié: (2025)

Training Implicit Generative Models via an Invariant Statistical Loss
par: de Frutos, José Manuel, et autres
Publié: (2024)

Note on the identification of total effect in Cluster-DAGs with cycles
par: Yvernes, Clément
Publié: (2025)

Identifiability by common backdoor in summary causal graphs of time series
par: Yvernes, Clément, et autres
Publié: (2025)

Statistical Inference for Misspecified Contextual Bandits
par: Guo, Yongyi, et autres
Publié: (2025)

About the Cost of Central Privacy in Density Estimation
par: Lalanne, Clément, et autres
Publié: (2023)

Identifiability of total effects from abstractions of time series causal graphs
par: Assaad, Charles K., et autres
Publié: (2023)

Stochastic Direct Search Method for Blind Resource Allocation
par: Achddou, Juliette, et autres
Publié: (2022)

Accelerated Online Risk-Averse Policy Evaluation in POMDPs with Theoretical Guarantees and Novel CVaR Bounds
par: Pariente, Yaacov, et autres
Publié: (2026)

Retraining as Approximate Bayesian Inference
par: Katz, Harrison
Publié: (2026)

Physics-informed machine learning as a kernel method
par: Doumèche, Nathan, et autres
Publié: (2024)

Bayesian Inference of Minimally Complex Models with Interactions of Arbitrary Order
par: de Mulatier, Clélia, et autres
Publié: (2020)

Le Cam Distortion: A Decision-Theoretic Framework for Robust Transfer Learning
par: Akdemir, Deniz
Publié: (2025)

Reasoning with Sampling: Cutting at Decision Points
par: Zhou, Felix, et autres
Publié: (2026)

Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
par: Dong, Zihan, et autres
Publié: (2026)

A clarification on the links between potential outcomes and do-interventions
par: de Lara, Lucas
Publié: (2023)