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Nikita Kotelevskii

Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules

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Feb 16, 2024
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Efficient Conformal Prediction under Data Heterogeneity

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Dec 25, 2023
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Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks

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Dec 18, 2023
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FedPop: A Bayesian Approach for Personalised Federated Learning

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Jun 07, 2022
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NUQ: Nonparametric Uncertainty Quantification for Deterministic Neural Networks

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Feb 07, 2022
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Monte Carlo Variational Auto-Encoders

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Jun 30, 2021
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MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference

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Feb 27, 2020
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