conftrace_
← Core AI
Artificial Intelligence › Core AI ›

Causal Inference

3,310 papers

Papers per year

Papers

Distinguishing Cause and Effect in Bivariate Structural Causal Models: A Systematic Investigation JMLR 2023
Augmented Transfer Regression Learning with Semi-non-parametric Nuisance Models JMLR 2023
High-Dimensional Inference for Generalized Linear Models with Hidden Confounding JMLR 2023
Causal Bandits for Linear Structural Equation Models JMLR 2023
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models JMLR 2023
Set-valued Classification with Out-of-distribution Detection for Many Classes JMLR 2023
Spatial Correspondence between Graph Neural Network-Segmented Images MIDL 2023
Improved multi-site Parkinson’s disease classification using neuroimaging data with counterfactual inference MIDL 2023
Intra- and Inter-Cellular Awareness for 3D Neuron Tracking and Segmentation in Large-Scale Connectomics MIDL 2023
Interpretable (not just posthoc-explainable) heterogeneous survivors bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions MLHC 2023
Uncovering the Varied Impact of Behavioral Change Messages on Population Groups MLHC 2023
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation NSDI 2023
SSNSheerinKavitha at SemEval-2023 Task 7: Semantic Rule Based Label Prediction Using TF-IDF and BM25 Techniques SEMEVAL 2023
SemEval-2023 Task 8: Causal Medical Claim Identification and Related PIO Frame Extraction from Social Media Posts SEMEVAL 2023
Transfer learning for individual treatment effect estimation UAI 2023
Do we become wiser with time? On causal equivalence with tiered background knowledge UAI 2023
Enhancing Treatment Effect Estimation: A Model Robust Approach Integrating Randomized Experiments and External Controls using the Double Penalty Integration Estimator UAI 2023
Adaptivity Complexity for Causal Graph Discovery UAI 2023
Functional causal Bayesian optimization UAI 2023
Nyström $M$-Hilbert-Schmidt independence criterion UAI 2023
Causal effect estimation from observational and interventional data through matrix weighted linear estimators UAI 2023
Variable importance matching for causal inference UAI 2023
Finding Invariant Predictors Efficiently via Causal Structure UAI 2023
BISCUIT: Causal Representation Learning from Binary Interactions UAI 2023
Causal information splitting: Engineering proxy features for robustness to distribution shifts UAI 2023