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Showing 26–50 of 90 papers

TitleStatusHype
Bayesian Autoregressive Online Change-Point Detection with Time-Varying ParametersCode0
Improving probabilistic forecasts of extreme wind speeds by training statistical post-processing models with weighted scoring rulesCode0
Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble ForecastsCode0
Combinations of distributional regression algorithms with application in uncertainty estimation of corrected satellite precipitation products—0
Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks—0
A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional DataCode0
VAEneu: A New Avenue for VAE Application on Probabilistic Forecasting—0
On Training Survival Models with Scoring Rules—0
Ads in Conversations—0
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors—0
Uncertainty estimation of machine learning spatial precipitation predictions from satellite data—0
Familiarity-Based Open-Set Recognition Under Adversarial Attacks—0
Determining Winners in Elections with Absent Votes—0
Using AI Uncertainty Quantification to Improve Human Decision-Making—0
Probabilistic Self-supervised Learning via Scoring Rules Minimization—0
SupEuclid: Extremely Simple, High Quality OoD Detection with Supervised Contrastive Learning and Euclidean Distance—0
A Novel Multiagent Flexibility Aggregation Framework—0
U-Calibration: Forecasting for an Unknown Agent—0
Regions of Reliability in the Evaluation of Multivariate Probabilistic ForecastsCode0
ProPanDL: A Modular Architecture for Uncertainty-Aware Panoptic Segmentation—0
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model—0
Uniform Pessimistic Risk and its Optimal Portfolio—0
Bayesian score calibration for approximate modelsCode0
Security-Preserving Federated Learning via Byzantine-Sensitive Triplet DistanceCode0
Generative machine learning methods for multivariate ensemble post-processingCode0
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