graphical model

On Model Selection Consistency of Lasso for High-Dimensional Ising Models AISTATS 2023 On Testability and Goodness of Fit Tests in Missing Data Models UAI 2023 Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications JMLR 2023 Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models AAAI 2023 Probabilistic Multi-Dimensional Classification UAI 2023 Regularized Joint Mixture Models JMLR 2023 Scalable Coupling of Deep Learning with Logical Reasoning IJCAI 2023 Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation AAAI 2023 Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs AAAI 2023 The Lauritzen-Chen Likelihood For Graphical Models AISTATS 2023 Tree-AMP: Compositional Inference with Tree Approximate Message Passing JMLR 2023 Unbiased learning of deep generative models with structured discrete representations NeurIPS 2023 Vector Causal Inference between Two Groups of Variables AAAI 2023 A Complete Criterion for Value of Information in Soluble Influence Diagrams AAAI 2022 Active Structure Learning of Bayesian Networks in an Observational Setting JMLR 2022 AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning ICLR 2022 Algorithmic Fairness Verification with Graphical Models AAAI 2022 AND/OR branch-and-bound for computational protein design optimizing K* UAI 2022 A new constructive criterion for Markov equivalence of MAGs UAI 2022 Approximate Inference for Stochastic Planning in Factored Spaces PGM 2022 Causal discovery under a confounder blanket UAI 2022 Causal Effect Identification with Context-specific Independence Relations of Control Variables AISTATS 2022 Causal Inference with Non-IID Data using Linear Graphical Models NeurIPS 2022 DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization NeurIPS 2022 Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems NeurIPS 2022