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Causal Inference

Causal inference is the task of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect.

( Image credit: Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data )

Papers

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Showing 251–300 of 1722 papers

TitleStatusHype
From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI—0
Attribution Projection Calculus: A Novel Framework for Causal Inference in Bayesian Networks—0
A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation—0
A Fast Kernel-based Conditional Independence test with Application to Causal Discovery—0
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference—0
Forests for Differences: Robust Causal Inference Beyond Parametric DiD—0
Empowering Vision Transformers with Multi-Scale Causal Intervention for Long-Tailed Image Classification—0
Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction—0
Causal knowledge graph analysis identifies adverse drug effects—0
Hillclimb-Causal Inference: A Data-Driven Approach to Identify Causal Pathways Among Parental Behaviors, Genetic Risk, and Externalizing Behaviors in ChildrenCode0
dcFCI: Robust Causal Discovery Under Latent Confounding, Unfaithfulness, and Mixed Data—0
Moments of Causal Effects—0
Scientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directions—0
Structure Causal Models and LLMs Integration in Medical Visual Question Answering—0
Federated Causal Inference in Healthcare: Methods, Challenges, and Applications—0
TV-SurvCaus: Dynamic Representation Balancing for Causal Survival Analysis—0
Causally Fair Node Classification on Non-IID Graph Data—0
Inference for max-linear Bayesian networks with noise—0
A Unifying Framework for Robust and Efficient Inference with Unstructured Data—0
On the Mechanistic Interpretability of Neural Networks for Causality in Bio-statisticsCode0
A Hamiltonian Higher-Order Elasticity Framework for Dynamic Diagnostics(2HOED)—0
Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions—0
Inference with few treated units—0
ReLU integral probability metric and its applications—0
Consistent Causal Inference of Group Effects in Non-Targeted Trials with Finitely Many Effect Levels—0
Causal DAG Summarization (Full Version)—0
Causality for Natural Language Processing—0
Dynamic Regularized CBDT: Variance-Calibrated Causal Boosting for Interpretable Heterogeneous Treatment Effects—0
Causal-Copilot: An Autonomous Causal Analysis Agent—0
Eco-efficiency as a Catalyst for Citizen Co-production: Evidence from Chinese Cities—0
The heterogeneous causal effects of the EU's Cohesion Fund—0
Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic EnvironmentsCode0
On relative universality, regression operator, and conditional independence—0
Reimagining Urban Science: Scaling Causal Inference with Large Language Models—0
A Two-Stage Interpretable Matching Framework for Causal Inference—0
A Framework of decision-relevant observability: Reinforcement Learning converges under relative ignorability—0
Double Machine Learning for Causal Inference under Shared-State InterferenceCode0
Better Decisions through the Right Causal World Model—0
Causal Inference under Interference through Designed Markets—0
Causal Inference Isn't Special: Why It's Just Another Prediction Problem—0
Counterfactual Inference under Thompson Sampling—0
A Causal Inference Framework for Data Rich Environments—0
PROPHET: An Inferable Future Forecasting Benchmark with Causal Intervened Likelihood EstimationCode0
Identifying Macro Causal Effects in C-DMGs—0
Causal Models for Growing Networks—0
Reinterpreting demand estimation—0
ClusterSC: Advancing Synthetic Control with Donor Selection—0
Inferring Treatment Effects in Large Panels by Uncovering Latent Similarities—0
Body Discovery of Embodied AI—0
Causal Links Between Anthropogenic Emissions and Air Pollution Dynamics in Delhi—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAverage Treatment Effect Error0.96—Unverified
2Balancing Linear RegressionAverage Treatment Effect Error0.93—Unverified
3k-NNAverage Treatment Effect Error0.79—Unverified
4CEVAEAverage Treatment Effect Error0.46—Unverified
5Balancing Neural NetworkAverage Treatment Effect Error0.42—Unverified
6Causal ForestAverage Treatment Effect Error0.4—Unverified
7BCAUS DRAverage Treatment Effect Error0.29—Unverified
8TARNetAverage Treatment Effect Error0.28—Unverified
9Counterfactual Regression + WASSAverage Treatment Effect Error0.27—Unverified
10MTDL-KNNAverage Treatment Effect Error0.23—Unverified
#ModelMetricClaimedVerifiedStatus
1CFR WASSAverage Treatment Effect on the Treated Error0.09—Unverified
2CFR MMDAverage Treatment Effect on the Treated Error0.08—Unverified
3BARTAverage Treatment Effect on the Treated Error0.08—Unverified
4GANITEAverage Treatment Effect on the Treated Error0.06—Unverified
5BCAUSSAverage Treatment Effect on the Treated Error0.05—Unverified
#ModelMetricClaimedVerifiedStatus
1BARTAverage Treatment Effect Error0.34—Unverified
2OLS with separate regressors for each treatmentAverage Treatment Effect Error0.31—Unverified
3Average Treatment Effect Error-0.23—Unverified