causal mechanism

Bayesian Hierarchical Invariant Prediction CLeaR 2026 Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation CLeaR 2025 Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms ICML 2025 Generalizable Single-Source Cross-Modality Medical Image Segmentation via Invariant Causal Mechanisms WACV 2025 Identifying Causal Mechanism Shifts Under Additive Models with Arbitrary Noise IJCAI 2025 Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors ICML 2025 Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference ICML 2024 Detecting and Measuring Confounding Using Causal Mechanism Shifts NeurIPS 2024 Graph Structure Extrapolation for Out-of-Distribution Generalization ICML 2024 Qualitative Mechanism Independence NeurIPS 2024 Causal Discovery in Semi-Stationary Time Series NeurIPS 2023 Detecting hidden confounding in observational data using multiple environments NeurIPS 2023 Do Not Marginalize Mechanisms, Rather Consolidate! NeurIPS 2023 Interpretability at Scale: Identifying Causal Mechanisms in Alpaca NeurIPS 2023 iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models NeurIPS 2023 Learning Optimal Features via Partial Invariance AAAI 2023 Multi-View Adversarial Discriminator: Mine the Non-Causal Factors for Object Detection in Unseen Domains CVPR 2023 Which Invariance Should We Transfer? A Causal Minimax Learning Approach ICML 2023 Bivariate Causal Discovery via Conditional Divergence CLeaR 2022 Identifying Coarse-grained Independent Causal Mechanisms with Self-supervision CLeaR 2022 Out-of-Distribution Generalization With Causal Invariant Transformations CVPR 2022 Partial disentanglement for domain adaptation ICML 2022 Properties from mechanisms: an equivariance perspective on identifiable representation learning ICLR 2022 ZIN: When and How to Learn Invariance Without Environment Partition? NeurIPS 2022 Counterfactual Generative Networks ICLR 2021