scoring rule

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Most implemented papers archive 2025-07-28

25 shown of 25 papers with code (90 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• NGBoost: Natural Gradient Boosting for Probabilistic Prediction
  8 Oct 2019 4 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  NGBoost generalizes gradient boosting to probabilistic regression by treating the parameters of the conditional distribution as targets for a multiparameter boosting algorithm.
• Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors
  13 Jan 2021 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  We show that in the context of object detection, training variance networks with negative log likelihood (NLL) can lead to high entropy predictive distributions regardless of the correctness of the output mean.
• Beyond calibration: estimating the grouping loss of modern neural networks
  28 Oct 2022 2 repositories listed
  Yet calibration is not enough: even a perfectly calibrated classifier with the best possible accuracy can have confidence scores that are far from the true posterior probabilities.
• Survival Regression with Proper Scoring Rules and Monotonic Neural Networks
  26 Mar 2021 2 repositories listed
  We consider frequently used scoring rules for right-censored survival regression models such as time-dependent concordance, survival-CRPS, integrated Brier score and integrated binomial log-likelihood, and prove that…
• A Spectral Energy Distance for Parallel Speech Synthesis
  3 Aug 2020 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Speech synthesis is an important practical generative modeling problem that has seen great progress over the last few years, with likelihood-based autoregressive neural models now outperforming traditional concatenative…
• h-calibration: Rethinking Classifier Recalibration with Probabilistic Error-Bounded Objective
  22 Jun 2025 1 repository listed
  In this study, we summarize and categorize previous works into three general strategies: intuitively designed methods, binning-based methods, and methods based on formulations of ideal calibration.
• Enforcing tail calibration when training probabilistic forecast models
  16 Jun 2025 1 repository listed
  We demonstrate that state-of-the-art models do not issue calibrated forecasts for extreme wind speeds, and that the calibration of forecasts for extreme events can be improved by suitable adaptations to the loss…
• Harnessing Superclasses for Learning from Hierarchical Databases
  25 Nov 2024 1 repository listed
  In many large-scale classification problems, classes are organized in a known hierarchy, typically represented as a tree expressing the inclusion of classes in superclasses.
• Superior Scoring Rules for Probabilistic Evaluation of Single-Label Multi-Class Classification Tasks
  25 Jul 2024 1 repository listed
  Traditional scoring rules like Brier Score and Logarithmic Loss sometimes assign better scores to misclassifications in comparison with correct classifications.
• Bayesian Autoregressive Online Change-Point Detection with Time-Varying Parameters
  23 Jul 2024 1 repository listed
  Building upon the Bayesian approach introduced in \cite{c:07}, we devise a new method for online change point detection in the mean of a univariate time series, which is well suited for real-time applications and is…
• Improving probabilistic forecasts of extreme wind speeds by training statistical post-processing models with weighted scoring rules
  22 Jul 2024 1 repository listed
  In this work we aim to improve statistical post-processing models for probabilistic predictions of extreme wind speeds.
• Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts
  2 Jul 2024 1 repository listed
  Accurate precipitation forecasts have a high socio-economic value due to their role in decision-making in various fields such as transport networks and farming.
• A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data
  6 Jun 2024 1 repository listed
  Evaluating on 8 survival metrics, we assess discrimination, calibration, and overall predictive performance of the tested models.
• Language Generation with Strictly Proper Scoring Rules
  29 May 2024 1 repository listed Syntology ran 5 of 6 samples · 1 unverified · 1 pointer-only (licence)
  Leveraging this strategy, we train language generation models using two classic strictly proper scoring rules, the Brier score and the Spherical score, as alternatives to the logarithmic score.
• Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
  19 Apr 2023 1 repository listed Syntology ran 0 of 19 samples · 19 unverified
  Multivariate probabilistic time series forecasts are commonly evaluated via proper scoring rules, i.
• Bayesian score calibration for approximate models
  10 Nov 2022 1 repository listed
  In this paper we propose a new method for adjusting approximate posterior samples to reduce bias and produce more accurate uncertainty quantification.
• Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance
  29 Oct 2022 1 repository listed
  While being an effective framework of learning a shared model across multiple edge devices, federated learning (FL) is generally vulnerable to Byzantine attacks from adversarial edge devices.
• Generative machine learning methods for multivariate ensemble post-processing
  26 Sep 2022 1 repository listed Syntology ran 0 of 4 samples · 4 unverified
  Ensemble weather forecasts based on multiple runs of numerical weather prediction models typically show systematic errors and require post-processing to obtain reliable forecasts.
• Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization
  31 May 2022 1 repository listed
  However, generative networks only allow sampling from the parametrized distribution; for this reason, Ramesh et al.
• Probabilistic Symmetry for Multi-Agent Dynamics
  4 May 2022 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  We propose a novel deep dynamics model, Probabilistic Equivariant Continuous COnvolution (PECCO) for probabilistic prediction of multi-agent trajectories.
• Object Detection as Probabilistic Set Prediction
  15 Mar 2022 1 repository listed
  Accurate uncertainty estimates are essential for deploying deep object detectors in safety-critical systems.
• Local Constraint-Based Causal Discovery under Selection Bias
  3 Mar 2022 1 repository listed
  We consider the problem of discovering causal relations from independence constraints selection bias in addition to confounding is present.
• Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization
  15 Dec 2021 1 repository listed
  Adversarial-free minimization is possible for some scoring rules; hence, our framework avoids the cumbersome hyperparameter tuning and uncertainty underestimation due to unstable adversarial training, thus unlocking…
• No-Regret and Incentive-Compatible Online Learning
  20 Feb 2020 1 repository listed
  First, we want the learning algorithm to be no-regret with respect to the best fixed expert in hindsight.
• Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective
  5 Mar 2019 1 repository listed
  Robust scatter estimation is a fundamental task in statistics.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.