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Causal Inference

3,310 papers

Papers per year

Papers

Estimating Causal Effects using a Multi-task Deep Ensemble ICML 2023
Detecting Out-of-distribution Data through In-distribution Class Prior ICML 2023
Approximate Causal Effect Identification under Weak Confounding ICML 2023
On the Expressive Power of Geometric Graph Neural Networks ICML 2023
Estimating Joint Treatment Effects by Combining Multiple Experiments ICML 2023
Nonlinear Causal Discovery with Latent Confounders ICML 2023
Instrumental Variable Estimation of Average Partial Causal Effects ICML 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning ICML 2023
Estimation Beyond Data Reweighting: Kernel Method of Moments ICML 2023
Propensity Matters: Measuring and Enhancing Balancing for Recommendation ICML 2023
Causal Structure Learning for Latent Intervened Non-stationary Data ICML 2023
Which Invariance Should We Transfer? A Causal Minimax Learning Approach ICML 2023
Additive Causal Bandits with Unknown Graph ICML 2023
Analyzing Diffusion as Serial Reproduction ICML 2023
Normalizing Flows for Interventional Density Estimation ICML 2023
Counterfactual Identifiability of Bijective Causal Models ICML 2023
The Statistical Scope of Multicalibration ICML 2023
B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding ICML 2023
PAC Generalization via Invariant Representations ICML 2023
Collaborative Causal Inference with Fair Incentives ICML 2023
DRCFS: Doubly Robust Causal Feature Selection ICML 2023
Improving Fair Training under Correlation Shifts ICML 2023
Statistical Inference on Multi-armed Bandits with Delayed Feedback ICML 2023
A Closer Look at the Intervention Procedure of Concept Bottleneck Models ICML 2023
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting ICML 2023