structural learning

Recursive Causal Discovery (Abstract Reprint) AAAI 2026 A Multi-Expert Structural-Semantic Hybrid Framework for Unveiling Historical Patterns in Temporal Knowledge Graphs ACL 2025 Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables JMLR 2025 Multi-identity Human Image Animation with Structural Video Diffusion ICCV 2025 Structural Patent Classification Using Label Hierarchy Optimization EMNLP 2025 A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences NeurIPS 2024 Learning Gaussian DAGs from Network Data JMLR 2024 Learning Structure-Aware Representations of Dependent Types NeurIPS 2024 Pruning neural network models for gene regulatory dynamics using data and domain knowledge NeurIPS 2024 Scores for Learning Discrete Causal Graphs with Unobserved Confounders AAAI 2024 ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks AAAI 2023 Federated Graph Semantic and Structural Learning IJCAI 2023 Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal ICML 2023 On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs ICML 2023 On Learning Necessary and Sufficient Causal Graphs NeurIPS 2023 SEAG: Structure-Aware Event Causality Generation ACL 2023 Highly Efficient Structural Learning of Sparse Staged Trees PGM 2022 Structural Agnostic Modeling: Adversarial Learning of Causal Graphs JMLR 2022 When, where, and how to add new neurons to ANNs AutoML 2022 Disentangling Online Chats with DAG-structured LSTMs ACL 2021 Matching a Desired Causal State via Shift Interventions NeurIPS 2021 An Attention-Based Graph Neural Network for Heterogeneous Structural Learning AAAI 2020 A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models AAAI 2020 Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks NeurIPS 2020 Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning NeurIPS 2020