probabilistic prediction

Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation CVPR 2025 Calibrated Regression Against An Adversary Without Regret UAI 2025 CoDiCast: Conditional Diffusion Model for Global Weather Forecasting with Uncertainty Quantification IJCAI 2025 Predicting Language Models’ Success at Zero-Shot Probabilistic Prediction EMNLP 2025 Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors AISTATS 2024 DNSMOS Pro: A Reduced-Size DNN for Probabilistic MOS of Speech Interspeech 2024 Faster Recalibration of an Online Predictor via Approachability AISTATS 2024 Linguistic Calibration of Long-Form Generations ICML 2024 MaxEnt Loss: Constrained Maximum Entropy for Calibration under Out-of-Distribution Shift AAAI 2024 Reciprocal Learning NeurIPS 2024 Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees NeurIPS 2024 Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning NeurIPS 2024 Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting UAI 2023 From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions JMLR 2023 Online Platt Scaling with Calibeating ICML 2023 Probabilistic Symmetry for Multi-Agent Dynamics L4DC 2023 Autoregressive Quantile Flows for Predictive Uncertainty Estimation ICLR 2022 Better Uncertainty Calibration via Proper Scores for Classification and Beyond NeurIPS 2022 Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation ICML 2022 Calibrated Learning to Defer with One-vs-All Classifiers ICML 2022 Gaussian Process Boosting JMLR 2022 Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees NeurIPS 2022 Metrics of Calibration for Probabilistic Predictions JMLR 2022 Modular Conformal Calibration ICML 2022 Stop Measuring Calibration When Humans Disagree EMNLP 2022