Probabilistic Modeling

Anytime User Engagement Prediction in Information Cascades for Arbitrary Observation Periods AAAI 2023 A Probabilistic Framework for Discovering New Intents ACL 2023 A Probabilistic Framework for Lifelong Test-Time Adaptation CVPR 2023 Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression NeurIPS 2023 Attention as Implicit Structural Inference NeurIPS 2023 Automatically marginalized MCMC in probabilistic programming ICML 2023 Bayesian Data Selection JMLR 2023 Bayesian Federated Neural Matching That Completes Full Information AAAI 2023 Bayesian Spiked Laplacian Graphs JMLR 2023 Bayesian Structure Scores for Probabilistic Circuits AISTATS 2023 B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding ICML 2023 Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations AAAI 2023 Bregman Deviations of Generic Exponential Families COLT 2023 Calibration by Distribution Matching: Trainable Kernel Calibration Metrics NeurIPS 2023 CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data ICML 2023 Causal Conditional Hidden Markov Model for Multimodal Traffic Prediction AAAI 2023 Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning ICLR 2023 Certifying Fairness of Probabilistic Circuits AAAI 2023 Characteristic Circuits NeurIPS 2023 C-NTPP: Learning Cluster-Aware Neural Temporal Point Process AAAI 2023 Combinatorial-Probabilistic Trade-Off: P-Values of Community Properties Test in the Stochastic Block Models ICLR 2023 Compositional Probabilistic and Causal Inference using Tractable Circuit Models AISTATS 2023 Compositional Score Modeling for Simulation-Based Inference ICML 2023 Compressing Tabular Data via Latent Variable Estimation ICML 2023 Computing Divergences between Discrete Decomposable Models AAAI 2023