Context-Specific Causal Graph Discovery with Unobserved Contexts: Non-Stationarity, Regimes and Spatio-Temporal Patterns
Fuente:
arXiv
Saved in:
| Main Authors: | Rabel, Martin, Runge, Jakob |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support
by: Rabel, Martin, et al.
Published: (2024)
by: Rabel, Martin, et al.
Published: (2024)
Causal discovery with endogenous context variables
by: Günther, Wiebke, et al.
Published: (2024)
by: Günther, Wiebke, et al.
Published: (2024)
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
by: Bing, Simon, et al.
Published: (2023)
by: Bing, Simon, et al.
Published: (2023)
Foundations of Causal Discovery on Groups of Variables
by: Wahl, Jonas, et al.
Published: (2023)
by: Wahl, Jonas, et al.
Published: (2023)
Estimation of Treatment Effects in Extreme and Unobserved Data
by: Tan, Jiyuan, et al.
Published: (2025)
by: Tan, Jiyuan, et al.
Published: (2025)
Functional Linear Non-Gaussian Acyclic Model for Causal Discovery
by: Yang, Tian-Le, et al.
Published: (2024)
by: Yang, Tian-Le, et al.
Published: (2024)
Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
by: Guan, Vincent, et al.
Published: (2024)
by: Guan, Vincent, et al.
Published: (2024)
Online Statistical Inference in Decision-Making with Matrix Context
by: Han, Qiyu, et al.
Published: (2022)
by: Han, Qiyu, et al.
Published: (2022)
On the Role of Depth and Looping for In-Context Learning with Task Diversity
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
Causal Inference on Process Graphs, Part II: Causal Structure and Effect Identification
by: Reiter, Nicolas-Domenic, et al.
Published: (2024)
by: Reiter, Nicolas-Domenic, et al.
Published: (2024)
Differentiable Structure Learning and Causal Discovery for General Binary Data
by: Deng, Chang, et al.
Published: (2025)
by: Deng, Chang, et al.
Published: (2025)
Transformers Meet In-Context Learning: A Universal Approximation Theory
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
Causal Discovery under Latent Class Confounding
by: Mazaheri, Bijan, et al.
Published: (2023)
by: Mazaheri, Bijan, et al.
Published: (2023)
Out-of-Distribution Generalization of In-Context Learning: A Low-Dimensional Subspace Perspective
by: Kwon, Soo Min, et al.
Published: (2025)
by: Kwon, Soo Min, et al.
Published: (2025)
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem
by: Even, Mathieu, et al.
Published: (2024)
by: Even, Mathieu, et al.
Published: (2024)
Long-Context Linear System Identification
by: Yüksel, Oğuz Kaan, et al.
Published: (2024)
by: Yüksel, Oğuz Kaan, et al.
Published: (2024)
Causal Inference on Process Graphs, Part I: The Structural Equation Process Representation
by: Reiter, Nicolas-Domenic, et al.
Published: (2023)
by: Reiter, Nicolas-Domenic, et al.
Published: (2023)
Hypothesis Testing over Observable Regimes in Singular Models
by: Plummer, Sean
Published: (2026)
by: Plummer, Sean
Published: (2026)
PAC-Chernoff Bounds: Understanding Generalization in the Interpolation Regime
by: Masegosa, Andrés R., et al.
Published: (2023)
by: Masegosa, Andrés R., et al.
Published: (2023)
Clustered Switchback Designs for Experimentation Under Spatio-temporal Interference
by: Jia, Su, et al.
Published: (2023)
by: Jia, Su, et al.
Published: (2023)
Learnable Conformal Prediction with Context-Aware Nonconformity Functions for Robotic Planning and Perception
by: Kumar, Divake, et al.
Published: (2025)
by: Kumar, Divake, et al.
Published: (2025)
Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
by: Hu, Hong, et al.
Published: (2024)
by: Hu, Hong, et al.
Published: (2024)
Jackknife Variance Estimation for Hájek-Dominated Generalized U-Statistics
by: Juergens, Jakob R.
Published: (2025)
by: Juergens, Jakob R.
Published: (2025)
Scaling Limits of Long-Context Transformers
by: Bruno, Giuseppe, et al.
Published: (2026)
by: Bruno, Giuseppe, et al.
Published: (2026)
Subgroup Discovery with the Cox Model
by: Izzo, Zachary, et al.
Published: (2025)
by: Izzo, Zachary, et al.
Published: (2025)
On Multiple Robustness of Proximal Dynamic Treatment Regimes
by: Gao, Yuanshan, et al.
Published: (2025)
by: Gao, Yuanshan, et al.
Published: (2025)
Further Understanding of a Local Gaussian Process Approximation: Characterising Convergence in the Finite Regime
by: Stephenson, Anthony, et al.
Published: (2024)
by: Stephenson, Anthony, et al.
Published: (2024)
Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods
by: Shen, Zhaiming, et al.
Published: (2025)
by: Shen, Zhaiming, et al.
Published: (2025)
Transformers Handle Endogeneity in In-Context Linear Regression
by: Liang, Haodong, et al.
Published: (2024)
by: Liang, Haodong, et al.
Published: (2024)
Representation of Context-Specific Causal Models with Observational and Interventional Data
by: Duarte, Eliana, et al.
Published: (2021)
by: Duarte, Eliana, et al.
Published: (2021)
Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes
by: Lau, Ivan, et al.
Published: (2026)
by: Lau, Ivan, et al.
Published: (2026)
Singular Fluctuation as Specific Heat in Bayesian Learning
by: Plummer, Sean
Published: (2025)
by: Plummer, Sean
Published: (2025)
Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime
by: Pandit, Parthe, et al.
Published: (2024)
by: Pandit, Parthe, et al.
Published: (2024)
Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
by: Elliott, Chris, et al.
Published: (2026)
by: Elliott, Chris, et al.
Published: (2026)
Higher-Order Causal Structure Learning with Additive Models
by: Enouen, James, et al.
Published: (2025)
by: Enouen, James, et al.
Published: (2025)
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
by: Guo, Siyuan, et al.
Published: (2022)
by: Guo, Siyuan, et al.
Published: (2022)
Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems
by: van Seeventer, Gijs, et al.
Published: (2026)
by: van Seeventer, Gijs, et al.
Published: (2026)
An introduction to Causal Modelling
by: Baishya, Gauranga Kumar
Published: (2025)
by: Baishya, Gauranga Kumar
Published: (2025)
Orthogonal Causal Calibration
by: Whitehouse, Justin, et al.
Published: (2024)
by: Whitehouse, Justin, et al.
Published: (2024)
Proximal Path-Specific Inference
by: Bai, Yang, et al.
Published: (2026)
by: Bai, Yang, et al.
Published: (2026)
Similar Items
-
Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support
by: Rabel, Martin, et al.
Published: (2024) -
Causal discovery with endogenous context variables
by: Günther, Wiebke, et al.
Published: (2024) -
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
by: Bing, Simon, et al.
Published: (2023) -
Foundations of Causal Discovery on Groups of Variables
by: Wahl, Jonas, et al.
Published: (2023) -
Estimation of Treatment Effects in Extreme and Unobserved Data
by: Tan, Jiyuan, et al.
Published: (2025)