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Tag: predictive

  • Design-marginal calibration of Gaussian process predictive distributions: Bayesian and conformal approaches

    Design-marginal calibration of Gaussian process predictive distributions: Bayesian and conformal approaches arXiv:2512.05611v1 Announce Type: new Abstract: We study the calibration of Gaussian process (GP) predictive distributions in the interpolation setting from a design-marginal perspective. Conditioning on the data and averaging over a design measure mu, we formalize mu-coverage for central intervals and mu-probabilistic calibration through…

  • GraphPPD: Posterior Predictive Modelling for Graph-Level Inference

    GraphPPD: Posterior Predictive Modelling for Graph-Level Inference arXiv:2508.16995v1 Announce Type: new Abstract: Accurate modelling and quantification of predictive uncertainty is crucial in deep learning since it allows a model to make safer decisions when the data is ambiguous and facilitates the users’ understanding of the model’s confidence in its predictions. Along with the tremendously increasing…

  • Model Predictive Control Basics

    Model Predictive Control Basics A hands-on tutorial with Python and CasADi The post Model Predictive Control Basics appeared first on Towards Data Science. Willem Esterhuizen Go to original source

  • Evasion Attacks Against Bayesian Predictive Models

    Evasion Attacks Against Bayesian Predictive Models arXiv:2506.09640v1 Announce Type: new Abstract: There is an increasing interest in analyzing the behavior of machine learning systems against adversarial attacks. However, most of the research in adversarial machine learning has focused on studying weaknesses against evasion or poisoning attacks to predictive models in classical setups, with the susceptibility…

  • Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric Perspective

    Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric Perspective arXiv:2412.09712v1 Announce Type: new Abstract: The Rashomon effect presents a significant challenge in model selection. It occurs when multiple models achieve similar performance on a dataset but produce different predictions, resulting in predictive multiplicity. This is especially problematic in high-stakes environments,…