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TitleStatusHype
NGBoost: Natural Gradient Boosting for Probabilistic PredictionCode2
Estimating and Evaluating Regression Predictive Uncertainty in Deep Object DetectorsCode1
Beyond calibration: estimating the grouping loss of modern neural networksCode1
Superior Scoring Rules for Probabilistic Evaluation of Single-Label Multi-Class Classification TasksCode1
h-calibration: Rethinking Classifier Recalibration with Probabilistic Error-Bounded ObjectiveCode1
A Spectral Energy Distance for Parallel Speech SynthesisCode1
Language Generation with Strictly Proper Scoring RulesCode1
Probabilistic Forecasting with Generative Networks via Scoring Rule MinimizationCode1
Bayesian score calibration for approximate modelsCode0
No-Regret and Incentive-Compatible Online LearningCode0
Object Detection as Probabilistic Set PredictionCode0
Harnessing Superclasses for Learning from Hierarchical DatabasesCode0
Likelihood-Free Inference with Generative Neural Networks via Scoring Rule MinimizationCode0
Local Constraint-Based Causal Discovery under Selection BiasCode0
Enforcing tail calibration when training probabilistic forecast modelsCode0
Improving probabilistic forecasts of extreme wind speeds by training statistical post-processing models with weighted scoring rulesCode0
A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional DataCode0
Survival Regression with Proper Scoring Rules and Monotonic Neural NetworksCode0
Probabilistic Symmetry for Multi-Agent DynamicsCode0
Regions of Reliability in the Evaluation of Multivariate Probabilistic ForecastsCode0
Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble ForecastsCode0
Bayesian Autoregressive Online Change-Point Detection with Time-Varying ParametersCode0
Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule PerspectiveCode0
Generative machine learning methods for multivariate ensemble post-processingCode0
Security-Preserving Federated Learning via Byzantine-Sensitive Triplet DistanceCode0
Incentives for Federated Learning: a Hypothesis Elicitation Approach—0
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model—0
Likelihood-Free Variational Autoencoders—0
Likelihood-ratio calibration using prior-weighted proper scoring rules—0
Uncertainty estimation of machine learning spatial precipitation predictions from satellite data—0
Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents—0
Model selection with Gini indices under auto-calibration—0
Multivariate Forecasting Evaluation: On Sensitive and Strictly Proper Scoring Rules—0
MVG-CRPS: A Robust Loss Function for Multivariate Probabilistic Forecasting—0
Online Aggregation of Probability Forecasts with Confidence—0
Online Learning with Continuous Ranked Probability Score—0
On the marginal likelihood and cross-validation—0
Optimal Scoring Rule Design under Partial Knowledge—0
Optimizing positional scoring rules for rank aggregation—0
Overlaying classifiers: a practical approach for optimal ranking—0
Predictive Indexing for Fast Search—0
Predictive Uncertainty in Deep Object Detectors: Estimation and Evaluation—0
Probabilistic Self-supervised Learning via Scoring Rules Minimization—0
ProPanDL: A Modular Architecture for Uncertainty-Aware Panoptic Segmentation—0
Proper-Composite Loss Functions in Arbitrary Dimensions—0
RDeepSense: Reliable Deep Mobile Computing Models with Uncertainty Estimations—0
Relationship between Hölder Divergence and Functional Density Power Divergence: Intersection and Generalization—0
Robust Estimation for Nonparametric Families via Generative Adversarial Networks—0
Scoring rule nets: beyond mean target prediction in multivariate regression—0
Scoring Strategic Agents—0
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