Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing
Fuente:
arXiv
Saved in:
| Main Authors: | Nguyen, Minh, Sabuncu, Mert R. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
by: Nguyen, Nang Hung, et al.
Published: (2026)
by: Nguyen, Nang Hung, et al.
Published: (2026)
GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Imaging Studies
by: Nguyen, Minh, et al.
Published: (2022)
by: Nguyen, Minh, et al.
Published: (2022)
Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning
by: Milecki, Leo, et al.
Published: (2026)
by: Milecki, Leo, et al.
Published: (2026)
Variable-Agnostic Causal Exploration for Reinforcement Learning
by: Nguyen, Minh Hoang, et al.
Published: (2024)
by: Nguyen, Minh Hoang, et al.
Published: (2024)
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
by: Rajendran, Suraj, et al.
Published: (2023)
by: Rajendran, Suraj, et al.
Published: (2023)
Motion Code: Robust Time Series Classification and Forecasting via Sparse Variational Multi-Stochastic Processes Learning
by: Bajaj, Chandrajit, et al.
Published: (2024)
by: Bajaj, Chandrajit, et al.
Published: (2024)
Causal Invariance and Counterfactual Learning Driven Cooperative Game for Multi-Label Classification
by: Fan, Yijia, et al.
Published: (2025)
by: Fan, Yijia, et al.
Published: (2025)
Efficient Ensemble Conditional Independence Test Framework for Causal Discovery
by: Guan, Zhengkang, et al.
Published: (2025)
by: Guan, Zhengkang, et al.
Published: (2025)
Enhancing Time Series Forecasting via a Parallel Hybridization of ARIMA and Polynomial Classifiers
by: Nguyen, Thanh Son, et al.
Published: (2025)
by: Nguyen, Thanh Son, et al.
Published: (2025)
Causal Manifold Fairness: Enforcing Geometric Invariance in Representation Learning
by: Rathore, Vidhi
Published: (2026)
by: Rathore, Vidhi
Published: (2026)
Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks
by: Shen, Rujia, et al.
Published: (2024)
by: Shen, Rujia, et al.
Published: (2024)
Efficient Transfer Learning via Causal Bounds
by: Gong, Xueping, et al.
Published: (2023)
by: Gong, Xueping, et al.
Published: (2023)
Efficient Latent Variable Causal Discovery: Combining Score Search and Targeted Testing
by: Ramsey, Joseph, et al.
Published: (2025)
by: Ramsey, Joseph, et al.
Published: (2025)
Adapting to Shifting Correlations with Unlabeled Data Calibration
by: Nguyen, Minh, et al.
Published: (2024)
by: Nguyen, Minh, et al.
Published: (2024)
Consistency of Neural Causal Partial Identification
by: Tan, Jiyuan, et al.
Published: (2024)
by: Tan, Jiyuan, et al.
Published: (2024)
SphUnc: Hyperspherical Uncertainty Decomposition and Causal Identification via Information Geometry
by: Fu, Rong, et al.
Published: (2026)
by: Fu, Rong, et al.
Published: (2026)
Decoupled Continuous-Time Reinforcement Learning via Hamiltonian Flow
by: Nguyen, Minh
Published: (2026)
by: Nguyen, Minh
Published: (2026)
Modeling Expert Interactions in Sparse Mixture of Experts via Graph Structures
by: Nguyen-Nhat, Minh-Khoi, et al.
Published: (2025)
by: Nguyen-Nhat, Minh-Khoi, et al.
Published: (2025)
Mitigating Prior Errors in Causal Structure Learning: A Resilient Approach via Bayesian Networks
by: Chen, Lyuzhou, et al.
Published: (2023)
by: Chen, Lyuzhou, et al.
Published: (2023)
Tagged for Direction: Pinning Down Causal Edge Directions with Precision
by: Busch, Florian Peter, et al.
Published: (2025)
by: Busch, Florian Peter, et al.
Published: (2025)
Content-Style Identification via Differential Independence
by: Timilsina, Subash, et al.
Published: (2026)
by: Timilsina, Subash, et al.
Published: (2026)
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
by: Wu, Yuxuan, et al.
Published: (2024)
by: Wu, Yuxuan, et al.
Published: (2024)
Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)
by: Shi, Zhihao, et al.
Published: (2025)
Continuous Invariance Learning
by: Lin, Yong, et al.
Published: (2023)
by: Lin, Yong, et al.
Published: (2023)
Improving Chain-of-Thought for Logical Reasoning via Attention-Aware Intervention
by: Phuong, Nguyen Minh, et al.
Published: (2026)
by: Phuong, Nguyen Minh, et al.
Published: (2026)
Optimal Experiments for Partial Causal Effect Identification
by: Maringgele, Tobias, et al.
Published: (2026)
by: Maringgele, Tobias, et al.
Published: (2026)
Causal Sensitivity Identification using Generative Learning
by: Bandyopadhyay, Soma, et al.
Published: (2025)
by: Bandyopadhyay, Soma, et al.
Published: (2025)
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error
by: Yang, Yuqin, et al.
Published: (2024)
by: Yang, Yuqin, et al.
Published: (2024)
R.I.P.: A Simple Black-box Attack on Continual Test-time Adaptation
by: Hoang, Trung-Hieu, et al.
Published: (2024)
by: Hoang, Trung-Hieu, et al.
Published: (2024)
Learning Structural Causal Models from Ordering: Identifiable Flow Models
by: Le, Minh Khoa, et al.
Published: (2024)
by: Le, Minh Khoa, et al.
Published: (2024)
Amortized Optimal Transport from Sliced Potentials
by: Truong, Minh-Phuc, et al.
Published: (2026)
by: Truong, Minh-Phuc, et al.
Published: (2026)
Causal Identification in Time Series Models
by: Jahn, Erik, et al.
Published: (2025)
by: Jahn, Erik, et al.
Published: (2025)
Local Causal Discovery for Statistically Efficient Causal Inference
by: Schubert, Mátyás, et al.
Published: (2025)
by: Schubert, Mátyás, et al.
Published: (2025)
Towards Error-Centric Intelligence II: Energy-Structured Causal Models
by: Thomas, Marcus
Published: (2025)
by: Thomas, Marcus
Published: (2025)
Efficient Differentiable Causal Discovery via Reliable Super-Structure Learning
by: Ma, Pingchuan, et al.
Published: (2026)
by: Ma, Pingchuan, et al.
Published: (2026)
Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification
by: Asiaee, Amir
Published: (2026)
by: Asiaee, Amir
Published: (2026)
Towards Layer-Wise Personalized Federated Learning: Adaptive Layer Disentanglement via Conflicting Gradients
by: Nguyen, Minh Duong, et al.
Published: (2024)
by: Nguyen, Minh Duong, et al.
Published: (2024)
Test Time Training for Supervised Causal Learning
by: Deng, Zizhen, et al.
Published: (2026)
by: Deng, Zizhen, et al.
Published: (2026)
Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
by: Nguyen, Huu Hiep, et al.
Published: (2026)
by: Nguyen, Huu Hiep, et al.
Published: (2026)
Causal Effect Identification in a Sub-Population with Latent Variables
by: Abouei, Amir Mohammad, et al.
Published: (2024)
by: Abouei, Amir Mohammad, et al.
Published: (2024)
Similar Items
-
Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
by: Nguyen, Nang Hung, et al.
Published: (2026) -
GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Imaging Studies
by: Nguyen, Minh, et al.
Published: (2022) -
Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning
by: Milecki, Leo, et al.
Published: (2026) -
Variable-Agnostic Causal Exploration for Reinforcement Learning
by: Nguyen, Minh Hoang, et al.
Published: (2024) -
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
by: Rajendran, Suraj, et al.
Published: (2023)