Image de couverture de livre

The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Emadi, Seyed Morteza
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence Information Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

The Critical Horizon: Inspection Design Principles for Multi-Stage Operations and Deep Reasoning
par: Emadi, Seyed Morteza
Publié: (2026)

Rank-Aware Spectral Bounds on Attention Logits for Stable Low-Precision Training
par: Emadi, Seyed Morteza
Publié: (2026)

Exact Attention Sensitivity and the Geometry of Transformer Stability
par: Emadi, Seyed Morteza
Publié: (2026)

The Causal Information Bottleneck and Optimal Causal Variable Abstractions
par: Simoes, Francisco N. F. Q., et autres
Publié: (2024)

An Information-Theoretic Criterion for Efficient Data Synthesis
par: Li, Hanyu, et autres
Publié: (2026)

An Effective Information Theoretic Framework for Channel Pruning
par: Chen, Yihao, et autres
Publié: (2024)

Machine Unlearning via Information Theoretic Regularization
par: Xu, Shizhou, et autres
Publié: (2025)

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
par: Laakom, Firas, et autres
Publié: (2025)

Information-Theoretic State Variable Selection for Reinforcement Learning
par: Westphal, Charles, et autres
Publié: (2024)

Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
par: Simeone, Osvaldo, et autres
Publié: (2025)

Context Channel Capacity: An Information-Theoretic Framework for Understanding Catastrophic Forgetting
par: Cheng, Ran
Publié: (2026)

Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective
par: Yang, Jiaming, et autres
Publié: (2026)

Information-Theoretic Policy Pre-Training with Empowerment
par: Schneider, Moritz, et autres
Publié: (2025)

On the Separability of Information in Diffusion Models
par: Premkumar, Akhil
Publié: (2025)

Probing the Information Theoretical Roots of Spatial Dependence Measures
par: Wang, Zhangyu, et autres
Publié: (2024)

Estimating Mutual Information between Time Series and Temporal Event Sequences Across Diverse Analysis Tasks
par: Hu, Haoji, et autres
Publié: (2026)

Neural Networks Learn Generic Multi-Index Models Near Information-Theoretic Limit
par: Zhang, Bohan, et autres
Publié: (2025)

Hierarchical Over-the-Air Federated Learning with Awareness of Interference and Data Heterogeneity
par: Azimi-Abarghouyi, Seyed Mohammad, et autres
Publié: (2024)

Scalable Hierarchical Over-the-Air Federated Learning
par: Azimi-Abarghouyi, Seyed Mohammad, et autres
Publié: (2022)

Over-the-Air Federated Learning via Weighted Aggregation
par: Azimi-Abarghouyi, Seyed Mohammad, et autres
Publié: (2024)

Compute-Update Federated Learning: A Lattice Coding Approach Over-the-Air
par: Azimi-Abarghouyi, Seyed Mohammad, et autres
Publié: (2024)

An Information Theoretic Perspective on Agentic System Design
par: He, Shizhe, et autres
Publié: (2025)

Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing
par: Azimi-Abarghouyi, Seyed Mohammad, et autres
Publié: (2025)

Causally-Guided Diffusion for Stable Feature Selection
par: Malarkkan, Arun Vignesh, et autres
Publié: (2026)

A General Error-Theoretical Analysis Framework for Constructing Compression Strategies
par: Zhang, Boyang, et autres
Publié: (2025)

Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
par: Rahman, Md Musfiqur, et autres
Publié: (2024)

The Agent Capability Problem: Predicting Solvability Through Information-Theoretic Bounds
par: Lutati, Shahar
Publié: (2025)

Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data
par: Yang, Yuqin, et autres
Publié: (2023)

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization
par: Amaefuna, Theophilus, et autres
Publié: (2026)

Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering
par: Ghodsi, Siamak, et autres
Publié: (2024)

Natural Latents: Latent Variables Stable Across Ontologies
par: Wentworth, John, et autres
Publié: (2025)

Learning What Matters: Adaptive Information-Theoretic Objectives for Robot Exploration
par: Yu, Youwei, et autres
Publié: (2026)

Laplace Sample Information: Data Informativeness Through a Bayesian Lens
par: Kaiser, Johannes, et autres
Publié: (2025)

Generalization and Informativeness of Conformal Prediction
par: Zecchin, Matteo, et autres
Publié: (2024)

Interpretable Diffusion via Information Decomposition
par: Kong, Xianghao, et autres
Publié: (2023)

An Information Criterion for Controlled Disentanglement of Multimodal Data
par: Wang, Chenyu, et autres
Publié: (2024)

Information-theoretic Bayesian Optimization: Survey and Tutorial
par: Garrido-Merchán, Eduardo C.
Publié: (2025)

A Rational Account of Categorization Based on Information Theory
par: MacLellan, Christopher J., et autres
Publié: (2026)

Entropy-informed Decoding: Adaptive Information-Driven Branching
par: Evans, Benjamin Patrick, et autres
Publié: (2026)

Partial Information Decomposition for Data Interpretability and Feature Selection
par: Westphal, Charles, et autres
Publié: (2024)