SOTAVerified

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 1501–1550 of 1722 papers

TitleStatusHype
Causally Fair Node Classification on Non-IID Graph Data—0
Causally-guided Regularization of Graph Attention Improves Generalizability—0
Causal Machine Learning for Healthcare and Precision Medicine—0
Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data—0
Causal Mediation Analysis with Hidden Confounders—0
Causal Model Analysis using Collider v-structure with Negative Percentage Mapping—0
Causal modelling without introducing counterfactuals or abstract distributions—0
Causal Models for Growing Networks—0
Causal models in string diagrams—0
Causal Multi-Level Fairness—0
Causal nearest neighbor rules for optimal treatment regimes—0
Causal Order Discovery based on Monotonic SCMs—0
Causal Probabilistic Spatio-temporal Fusion Transformers in Two-sided Ride-Hailing Markets—0
Causal programming: inference with structural causal models as finding instances of a relation—0
Causal Q-Aggregation for CATE Model Selection—0
Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks—0
Causal Reasoning in Software Quality Assurance: A Systematic Review—0
Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity—0
Causal Relational Learning—0
Causal Representation Learning with Generative Artificial Intelligence: Application to Texts as Treatments—0
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect Estimation—0
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect—0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach—0
Causal Structure Recovery of Linear Dynamical Systems: An FFT based Approach—0
Causal Triple Attention Time Series Forecasting—0
Analyzing User Characteristics of Hate Speech Spreaders on Social Media—0
Causal versions of Maximum Entropy and Principle of Insufficient Reason—0
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates—0
Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations—0
Causes of evolutionary divergence in prostate cancer—0
CauSkelNet: Causal Representation Learning for Human Behaviour Analysis—0
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference—0
CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems—0
Chemical Property Prediction Under Experimental Biases—0
CIER: A Novel Experience Replay Approach with Causal Inference in Deep Reinforcement Learning—0
Classifying Treatment Responders Under Causal Effect Monotonicity—0
Closing the loop on multisensory interactions: A neural architecture for multisensory causal inference and recalibration—0
ClusterSC: Advancing Synthetic Control with Donor Selection—0
Coarsened confounding for causal effects: a large-sample framework—0
Collaborative causal inference on distributed data—0
Collaborative-controlled LASSO for Constructing Propensity Score-based Estimators in High-Dimensional Data—0
Collaborative Heterogeneous Causal Inference Beyond Meta-analysis—0
Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects—0
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision—0
Comment on "Blessings of Multiple Causes"—0
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions—0
Complementary Advantages of ChatGPTs and Human Readers in Reasoning: Evidence from English Text Reading Comprehension—0
Compositional Models for Estimating Causal Effects—0
Computational Causal Inference—0
Computational identification of ketone metabolism as a key regulator of sleep stability and circadian dynamics via real-time metabolic profiling—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