Image de couverture de livre

Structural Causal Bottleneck Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Bing, Simon, Wahl, Jonas, Runge, Jakob
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
par: Bing, Simon, et autres
Publié: (2023)

Separation-based distance measures for causal graphs
par: Wahl, Jonas, et autres
Publié: (2024)

Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery
par: Herman, Rebecca J., et autres
Publié: (2025)

How PC-based Methods Err: Towards Better Reporting of Assumption Violations and Small Sample Errors
par: Faltenbacher, Sofia, et autres
Publié: (2025)

Sanity Checking Causal Representation Learning on a Simple Real-World System
par: Gamella, Juan L., et autres
Publié: (2025)

Using Time Structure to Estimate Causal Effects
par: Hochsprung, Tom, et autres
Publié: (2025)

Context-Specific Causal Graph Discovery with Unobserved Contexts: Non-Stationarity, Regimes and Spatio-Temporal Patterns
par: Rabel, Martin, et autres
Publié: (2025)

Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support
par: Rabel, Martin, et autres
Publié: (2024)

Foundations of Causal Discovery on Groups of Variables
par: Wahl, Jonas, et autres
Publié: (2023)

Causal Inference on Process Graphs, Part II: Causal Structure and Effect Identification
par: Reiter, Nicolas-Domenic, et autres
Publié: (2024)

Causal Inference on Process Graphs, Part I: The Structural Equation Process Representation
par: Reiter, Nicolas-Domenic, et autres
Publié: (2023)

Causally Reliable Concept Bottleneck Models
par: De Felice, Giovanni, et autres
Publié: (2025)

Causal discovery with endogenous context variables
par: Günther, Wiebke, et autres
Publié: (2024)

Causal discovery on vector-valued variables and consistency-guided aggregation
par: Ninad, Urmi, et autres
Publié: (2025)

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
par: Brouillard, Philippe, et autres
Publié: (2024)

Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)
par: Lade, Ankit Hemant, et autres
Publié: (2026)

Causal Representation Learning in Temporal Data via Single-Parent Decoding
par: Brouillard, Philippe, et autres
Publié: (2024)

Causally-Aware Information Bottleneck for Domain Adaptation
par: Javidian, Mohammad Ali
Publié: (2026)

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

There Was Never a Bottleneck in Concept Bottleneck Models
par: Almudévar, Antonio, et autres
Publié: (2025)

Bootstrap aggregation and confidence measures to improve time series causal discovery
par: Debeire, Kevin, et autres
Publié: (2023)

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
par: S, Saranya Ganesh, et autres
Publié: (2025)

A Probabilistic Framework for LLM-Based Model Discovery
par: Wahl, Stefan, et autres
Publié: (2026)

Asymptotic Uncertainty in the Estimation of Frequency Domain Causal Effects for Linear Processes
par: Reiter, Nicolas-Domenic, et autres
Publié: (2024)

Concepts' Information Bottleneck Models
par: Galliamov, Karim, et autres
Publié: (2026)

Matryoshka Concept Bottleneck Models
par: Chen, Ziye, et autres
Publié: (2026)

Controllable Concept Bottleneck Models
par: Lin, Hongbin, et autres
Publié: (2026)

Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
par: Rao, Jiahua, et autres
Publié: (2024)

Standardizing Structural Causal Models
par: Ormaniec, Weronika, et autres
Publié: (2024)

Stochastic Concept Bottleneck Models
par: Vandenhirtz, Moritz, et autres
Publié: (2024)

Graph Concept Bottleneck Models
par: Xu, Haotian, et autres
Publié: (2025)

Concept Bottleneck Models Without Predefined Concepts
par: Schrodi, Simon, et autres
Publié: (2024)

Causal-INSIGHT: Probing Temporal Models to Extract Causal Structure
par: Redden, Benjamin, et autres
Publié: (2026)

Refining the Information Bottleneck via Adversarial Information Separation
par: Ning, Shuai, et autres
Publié: (2026)

Credal Concept Bottleneck Models: Structural Separation of Epistemic and Aleatoric Uncertainty
par: Mukherjee, Tanmoy, et autres
Publié: (2026)

Coarse-to-Fine Concept Bottleneck Models
par: Panousis, Konstantinos P., et autres
Publié: (2023)

Individual Causal Inference with Structural Causal Model
par: Chang, Daniel T.
Publié: (2025)

Structured IB: Improving Information Bottleneck with Structured Feature Learning
par: Yang, Hanzhe, et autres
Publié: (2024)

If Concept Bottlenecks are the Question, are Foundation Models the Answer?
par: Debole, Nicola, et autres
Publié: (2025)

Diverse Concept Proposals for Concept Bottleneck Models
par: Brown, Katrina, et autres
Publié: (2024)