Calibration of deep probabilistic models with decoupled bayesian neural networks von Maroñas, Juan, Paredes, Roberto, Ramos, Daniel

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Improving calibration of forensic glass comparisons by considering uncertainty in feature-based elemental data von Ramos, Daniel, Maroñas, Juan, Almirall, Jose

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Gaussianization of LA-ICP-MS features to improve calibration in forensic glass comparison von Ramirez-Hereza, Pablo, Ramos, Daniel, Maroñas, Juan, Balanya, Sergio A., Almirall, Jose

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Adaptive temperature scaling for Robust calibration of deep neural networks von Balanya, Sergio A., Maroñas, Juan, Ramos, Daniel

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A deep analysis on high‐resolution dermoscopic image classification von Pollastri, Federico, Parreño, Mario, Maroñas, Juan, Bolelli, Federico, Paredes, Roberto, Ramos, Daniel, Grana, Costantino

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On Calibration of Mixup Training for Deep Neural Networks von Maroñas, Juan, Ramos, Daniel, Paredes, Roberto

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Generative Models for Deep Learning with Very Scarce Data von Maroñas, Juan, Paredes, Roberto, Ramos, Daniel

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Modeling Uncertainty for Reliable Probabilistic Modeling in Deep Learning and Beyond von Maroñas Molano, Juan

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Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification von Maroñas, Juan, Hernández-Lobato, Daniel

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Towards Flexibility and Interpretability of Gaussian Process State-Space Model von Lin, Zhid, Yin, Feng, Maroñas, Juan

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Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks von Balanya, Sergio A, Maroñas, Juan, Ramos, Daniel

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Deep Transformed Gaussian Processes von Sáez-Maldonado, Francisco Javier, Maroñas, Juan, Hernández-Lobato, Daniel

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Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models von Lin, Zhidi, Maroñas, Juan, Li, Ying, Yin, Feng, Theodoridis, Sergios

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On Calibration of Mixup Training for Deep Neural Networks von Maroñas, Juan, Ramos, Daniel, Paredes, Roberto

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Solving Partial Differential Equations with Neural Networks von Pedro, Juan B, Maroñas, Juan, Paredes, Roberto

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Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks von Maroñas, Juan, Paredes, Roberto, Ramos, Daniel

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Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification von Maroñas, Juan, Hernández-Lobato, Daniel

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Bayesian Strategies for Likelihood Ratio Computation in Forensic Voice Comparison with Automatic Systems von Ramos, Daniel, Maroñas, Juan, Lozano-Diez, Alicia

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Towards Flexibility and Interpretability of Gaussian Process State-Space Model von Lin, Zhid, Yin, Feng, Maroñas, Juan

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Generative Models For Deep Learning with Very Scarce Data von Maroñas, Juan, Paredes, Roberto, Ramos, Daniel

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