causal model

Abstractions in Causal Models and Game Structures CLeaR 2026 One Model to Rule Them All: Canonically Gluing Causal Models Along Shared Substructures UAI 2026 A Non-Interventionist Approach to Causal Reasoning Based on Lewisian Counterfactuals IJCAI 2025 Causal Models for Growing Networks UAI 2025 Counterfactual Token Generation in Large Language Models CLeaR 2025 DAGs as Minimal I-maps for the Induced Models of Causal Bayesian Networks under Conditioning JMLR 2025 Generating Synthetic Relational Tabular Data via Structural Causal Models ACL 2025 Local Interference: Removing Interference Bias in Semi-Parametric Causal Models CLeaR 2025 Real-time TSE demonstration via SoundBeam with KD Interspeech 2025 Relational Causal Discovery with Latent Confounders UAI 2025 Achievable distributional robustness when the robust risk is only partially identified NeurIPS 2024 An Information-Flow Perspective on Algorithmic Fairness AAAI 2024 Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion NeurIPS 2024 Discovering Agents (Abstract Reprint) AAAI 2024 Enhancing Evolving Domain Generalization through Dynamic Latent Representations AAAI 2024 InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques NeurIPS 2024 Learning Discrete Concepts in Latent Hierarchical Models NeurIPS 2024 Learning Truncated Causal History Model for Video Restoration NeurIPS 2024 Measuring Goal-Directedness NeurIPS 2024 Multiply-Robust Causal Change Attribution ICML 2024 Position: The Causal Revolution Needs Scientific Pragmatism ICML 2024 RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-Centric Learning WACV 2024 When is Transfer Learning Possible? ICML 2024 Differentiable Multi-Target Causal Bayesian Experimental Design ICML 2023 Identifiability Guarantees for Causal Disentanglement from Soft Interventions NeurIPS 2023