The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
Fuente:
arXiv
Saved in:
| Main Authors: | Brouillard, Philippe, Squires, Chandler, Wahl, Jonas, Kording, Konrad P., Sachs, Karen, Drouin, Alexandre, Sridhar, Dhanya |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Synthetic Potential Outcomes and Causal Mixture Identifiability
by: Mazaheri, Bijan, et al.
Published: (2024)
by: Mazaheri, Bijan, et al.
Published: (2024)
Foundations of Causal Discovery on Groups of Variables
by: Wahl, Jonas, et al.
Published: (2023)
by: Wahl, Jonas, et al.
Published: (2023)
Causal Representation Learning in Temporal Data via Single-Parent Decoding
by: Brouillard, Philippe, et al.
Published: (2024)
by: Brouillard, Philippe, et al.
Published: (2024)
Nonlinear Causal Discovery for Grouped Data
by: Göbler, Konstantin, et al.
Published: (2025)
by: Göbler, Konstantin, et al.
Published: (2025)
Causal Discovery on Dependent Binary Data
by: Chen, Alex, et al.
Published: (2024)
by: Chen, Alex, et al.
Published: (2024)
Causal-learn: Causal Discovery in Python
by: Zheng, Yujia, et al.
Published: (2023)
by: Zheng, Yujia, et al.
Published: (2023)
Self-Compatibility: Evaluating Causal Discovery without Ground Truth
by: Faller, Philipp M., et al.
Published: (2023)
by: Faller, Philipp M., et al.
Published: (2023)
Operationalizing Longitudinal Causal Discovery Under Real-World Workflow Constraints
by: Okuda, Tadahisa, et al.
Published: (2026)
by: Okuda, Tadahisa, et al.
Published: (2026)
Local Causal Discovery for Estimating Causal Effects
by: Gupta, Shantanu, et al.
Published: (2023)
by: Gupta, Shantanu, et al.
Published: (2023)
Partially Observed Structural Causal Models
by: Orujlu, Turan, et al.
Published: (2026)
by: Orujlu, Turan, et al.
Published: (2026)
CausalFormer: An Interpretable Transformer for Temporal Causal Discovery
by: Kong, Lingbai, et al.
Published: (2024)
by: Kong, Lingbai, et al.
Published: (2024)
Stable Differentiable Causal Discovery
by: Nazaret, Achille, et al.
Published: (2023)
by: Nazaret, Achille, et al.
Published: (2023)
Unsupervised Pairwise Causal Discovery on Heterogeneous Data using Mutual Information Measures
by: Trilla, Alexandre, et al.
Published: (2024)
by: Trilla, Alexandre, et al.
Published: (2024)
Invariant Causal Set Covering Machines
by: Godon, Thibaud, et al.
Published: (2023)
by: Godon, Thibaud, et al.
Published: (2023)
Evaluating Interventional Reasoning Capabilities of Large Language Models
by: Kasetty, Tejas, et al.
Published: (2024)
by: Kasetty, Tejas, et al.
Published: (2024)
Valid Inference After Causal Discovery
by: Gradu, Paula, et al.
Published: (2022)
by: Gradu, Paula, et al.
Published: (2022)
Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding
by: Schkoda, Daniela, et al.
Published: (2024)
by: Schkoda, Daniela, et al.
Published: (2024)
Multi-Domain Causal Discovery in Bijective Causal Models
by: Jalaldoust, Kasra, et al.
Published: (2025)
by: Jalaldoust, Kasra, et al.
Published: (2025)
RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model
by: Li, Peiwen, et al.
Published: (2024)
by: Li, Peiwen, et al.
Published: (2024)
Amortized Causal Discovery with Prior-Fitted Networks
by: Sypniewski, Mateusz, et al.
Published: (2025)
by: Sypniewski, Mateusz, et al.
Published: (2025)
Causal Graph Aided Causal Discovery in an Observational Aneurysmal Subarachnoid Hemorrhage Study
by: Berzuini, Carlo, et al.
Published: (2024)
by: Berzuini, Carlo, et al.
Published: (2024)
Conditional Local Independence Testing for Itô processes with Applications to Dynamic Causal Discovery
by: Liu, Mingzhou, et al.
Published: (2025)
by: Liu, Mingzhou, et al.
Published: (2025)
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
by: Maasch, Jacqueline, et al.
Published: (2023)
by: Maasch, Jacqueline, et al.
Published: (2023)
Federated Causal Discovery From Interventions
by: Abyaneh, Amin, et al.
Published: (2022)
by: Abyaneh, Amin, et al.
Published: (2022)
PAIR-CI: Calibrated Conditional Independence Testing for Causal Discovery with Incomplete Data
by: Robinson, Thomas S., et al.
Published: (2026)
by: Robinson, Thomas S., et al.
Published: (2026)
$\texttt{causalAssembly}$: Generating Realistic Production Data for Benchmarking Causal Discovery
by: Göbler, Konstantin, et al.
Published: (2023)
by: Göbler, Konstantin, et al.
Published: (2023)
Structural Causality-based Generalizable Concept Discovery Models
by: Sinha, Sanchit, et al.
Published: (2024)
by: Sinha, Sanchit, et al.
Published: (2024)
Causal Discovery and Classification Using Lempel-Ziv Complexity
by: Dhruthi, et al.
Published: (2024)
by: Dhruthi, et al.
Published: (2024)
Reinforcement Learning for Causal Discovery without Acyclicity Constraints
by: Duong, Bao, et al.
Published: (2024)
by: Duong, Bao, et al.
Published: (2024)
A Meta-Learning Approach to Bayesian Causal Discovery
by: Dhir, Anish, et al.
Published: (2024)
by: Dhir, Anish, et al.
Published: (2024)
Differentiable Cyclic Causal Discovery Under Unmeasured Confounders
by: Sethuraman, Muralikrishnna G., et al.
Published: (2025)
by: Sethuraman, Muralikrishnna G., et al.
Published: (2025)
Differentiable Structure Learning and Causal Discovery for General Binary Data
by: Deng, Chang, et al.
Published: (2025)
by: Deng, Chang, et al.
Published: (2025)
Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
by: Ng, Woon Yee, et al.
Published: (2025)
by: Ng, Woon Yee, et al.
Published: (2025)
Causal Discovery in Dynamic Fading Wireless Networks
by: Giwa, Oluwaseyi
Published: (2025)
by: Giwa, Oluwaseyi
Published: (2025)
Causal Discovery with Fewer Conditional Independence Tests
by: Shiragur, Kirankumar, et al.
Published: (2024)
by: Shiragur, Kirankumar, et al.
Published: (2024)
Scalable Variational Causal Discovery Unconstrained by Acyclicity
by: Hoang, Nu, et al.
Published: (2024)
by: Hoang, Nu, et al.
Published: (2024)
Interventional Causal Discovery in a Mixture of DAGs
by: Varıcı, Burak, et al.
Published: (2024)
by: Varıcı, Burak, et al.
Published: (2024)
The Robustness of Differentiable Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2025)
by: Yi, Huiyang, et al.
Published: (2025)
Stable Causal Discovery via Directed Acyclic Graph Aggregation
by: Wu, Yunan, et al.
Published: (2026)
by: Wu, Yunan, et al.
Published: (2026)
Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery
by: Waxman, Daniel, et al.
Published: (2024)
by: Waxman, Daniel, et al.
Published: (2024)
Similar Items
-
Synthetic Potential Outcomes and Causal Mixture Identifiability
by: Mazaheri, Bijan, et al.
Published: (2024) -
Foundations of Causal Discovery on Groups of Variables
by: Wahl, Jonas, et al.
Published: (2023) -
Causal Representation Learning in Temporal Data via Single-Parent Decoding
by: Brouillard, Philippe, et al.
Published: (2024) -
Nonlinear Causal Discovery for Grouped Data
by: Göbler, Konstantin, et al.
Published: (2025) -
Causal Discovery on Dependent Binary Data
by: Chen, Alex, et al.
Published: (2024)