{"total":21,"rows":[{"id":"2403.07185","title":"Uncertainty in Graph Neural Networks: A Survey","created":"2024-03-11","cited_by_count":23,"area":null},{"id":"2303.04040","title":"Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks","created":"2023-03-07","cited_by_count":12,"area":null},{"id":"2409.16586","title":"AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting","created":"2024-09-25","cited_by_count":10,"area":null},{"id":"2309.05072","title":"Uncertainty-Aware Probabilistic Graph Neural Networks for Road-Level Traffic Accident Prediction","created":"2023-09-10","cited_by_count":8,"area":null},{"id":"2401.13335","title":"Full Bayesian Significance Testing for Neural Networks","created":"2024-01-24","cited_by_count":8,"area":null},{"id":"2508.08551","title":"UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction","created":"2025-08-12","cited_by_count":8,"area":null},{"id":"2602.05286","title":"HealthMamba: An Uncertainty-aware Spatiotemporal Graph State Space Model for Effective and Reliable Healthcare Facility Visit Prediction","created":"2026-02-05","cited_by_count":8,"area":null},{"id":"2303.09273","title":"Adaptive Modeling of Uncertainties for Traffic Forecasting","created":"2023-03-16","cited_by_count":6,"area":null},{"id":"2401.10518","title":"Spatial-temporal Forecasting for Regions without Observations","created":"2024-01-19","cited_by_count":6,"area":null},{"id":"2307.05946","title":"A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models","created":"2023-07-12","cited_by_count":5,"area":null},{"id":"2409.08766","title":"SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks","created":"2024-09-13","cited_by_count":5,"area":null},{"id":"2601.13422","title":"TrustEnergy: A Unified Framework for Accurate and Reliable User-level Energy Usage Prediction","created":"2026-01-19","cited_by_count":5,"area":null},{"id":"2509.04623","title":"Split Conformal Prediction in the Function Space with Neural Operators","created":"2025-09-04","cited_by_count":4,"area":null},{"id":"2410.15241","title":"Conditional Uncertainty Quantification for Tensorized Topological Neural Networks","created":"2024-10-20","cited_by_count":3,"area":null},{"id":"2503.04981","title":"Topology-Aware Conformal Prediction for Stream Networks","created":"2025-03-06","cited_by_count":3,"area":null},{"id":"2403.07022","title":"A Unified Model for Spatio-Temporal Prediction Queries with Arbitrary Modifiable Areal Units","created":"2024-03-10","cited_by_count":2,"area":null},{"id":"2408.13293","title":"Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction","created":"2024-08-23","cited_by_count":1,"area":null},{"id":"2602.06866","title":"T-STAR: A Context-Aware Transformer Framework for Short-Term Probabilistic Demand Forecasting in Dock-Based Shared Micro-Mobility","created":"2026-02-06","cited_by_count":1,"area":null},{"id":"2412.04733","title":"A Survey and Benchmarking of Spatial-Temporal Traffic Data Imputation Models","created":"2024-12-06","cited_by_count":0,"area":null},{"id":"2605.25004","title":"Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data","created":"2026-05-24","cited_by_count":0,"area":null},{"id":"2605.28507","title":"Universal Time Series Generation with Neural Controlled Differential Equations","created":"2026-05-27","cited_by_count":0,"area":null}],"next_cursor":null}