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Measures and manages uncertainties in model predictions. Enhances decision-making by providing confidence levels in computer vision tasks.
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 Variational bagging: a robust approach for Bayesian uncertainty quantification Shitao Fan Ilsang Ohn David Dunson Lizhen Lin | |||
 Deep Gaussian Process Proximal Policy Optimization Matthijs van der Lende Juan Cardenas-Cartagena | |||
 When Active Learning Fails, Uncalibrated Out of Distribution Uncertainty Quantification Might Be the Problem Ashley S. Dale Kangming Li Brian DeCost Hao Wan Yuchen Han Yao Fehlis Jason Hattrick-Simpers | |||
 Neural Variational Dropout ProcessesInternational Conference on Learning Representations (ICLR), 2025 | |||
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