Causal Identification
8 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Causal Identification
BCOPA-CE
Most implemented papers
Adapting Text Embeddings for Causal Inference
blei-lab/causal-text-embeddings
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To address this challenge, we develop causally sufficient embeddings, low-dimensional document representations that preserve sufficient information for causal identification and allow for efficient estimation of causal effects.
The Causal-Neural Connection: Expressiveness, Learnability, and Inference
causalailab/neuralcausalmodels
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NeurIPS 2021
Given this property, one may be tempted to surmise that a collection of neural nets is capable of learning any SCM by training on data generated by that SCM.
Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach
Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system.
Identifying Causal Structure in Dynamical Systems
In this paper, we propose a method that identifies the causal structure of control systems.
Invariant Representation Learning for Treatment Effect Estimation
To address this challenge, practitioners collect and adjust for the covariates, hoping that they adequately correct for confounding.
Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
Recent work has focused on the potential and pitfalls of causal identification in observational studies with multiple simultaneous treatments.
The Effect of Noise Level on Causal Identification with Additive Noise Models
Unfortunately, one aspect of these methods has not received much attention until now: what is the impact of different noise levels on the ability of these methods to identify the direction of the causal relationship.
Flow-based Perturbation for Cause-effect Inference
ShaogangRen/EFRE
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Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM) 2022
A new causal discovery method is introduced to solve the bivariate causal discovery problem.
