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Juan Maroñas Molano
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2020 – today
- 2024
- [j3]Sérgio A. Balanya
, Juan Maroñas, Daniel Ramos:
Adaptive temperature scaling for Robust calibration of deep neural networks. Neural Comput. Appl. 36(14): 8073-8095 (2024) - [c6]Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis:
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models. ICASSP 2024: 12881-12885 - 2023
- [c5]Juan Maroñas, Daniel Hernández-Lobato:
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification. ICML 2023: 24045-24081 - [i10]Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis:
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models. CoRR abs/2309.01074 (2023) - [i9]Francisco Javier Sáez-Maldonado, Juan Maroñas, Daniel Hernández-Lobato:
Deep Transformed Gaussian Processes. CoRR abs/2310.18230 (2023) - 2022
- [i8]Juan Maroñas, Daniel Hernández-Lobato:
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification. CoRR abs/2205.15008 (2022) - [i7]Sérgio A. Balanya, Juan Maroñas, Daniel Ramos:
Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks. CoRR abs/2208.00461 (2022) - 2021
- [j2]Federico Pollastri, Mario Parreño, Juan Maroñas, Federico Bolelli, Roberto Paredes, Daniel Ramos, Costantino Grana:
A deep analysis on high-resolution dermoscopic image classification. IET Comput. Vis. 15(7): 514-526 (2021) - [c4]Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas:
Transforming Gaussian Processes With Normalizing Flows. AISTATS 2021: 1081-1089 - 2020
- [j1]Juan Maroñas
Calibration of deep probabilistic models with decoupled bayesian neural networks. Neurocomputing 407: 194-205 (2020) - [c3]Federico Pollastri, Juan Maroñas, Federico Bolelli, Giulia Ligabue, Roberto Paredes, Riccardo Magistroni, Costantino Grana:
Confidence Calibration for Deep Renal Biopsy Immunofluorescence Image Classification. ICPR 2020: 1298-1305 - [c2]Juan Maroñas
On Calibration of Mixup Training for Deep Neural Networks. S+SSPR 2020: 67-76 - [i6]Juan Maroñas, Daniel Ramos, Roberto Paredes:
Improving Calibration in Mixup-trained Deep Neural Networks through Confidence-Based Loss Functions. CoRR abs/2003.09946 (2020) - [i5]Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas:
Transforming Gaussian Processes With Normalizing Flows. CoRR abs/2011.01596 (2020)
2010 – 2019
- 2019
- [i4]Juan Maroñas Molano, Roberto Paredes, Daniel Ramos:
Generative Models For Deep Learning with Very Scarce Data. CoRR abs/1903.09030 (2019) - [i3]Juan Maroñas, Roberto Paredes, Daniel Ramos:
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks. CoRR abs/1908.08972 (2019) - [i2]Daniel Ramos, Juan Maroñas, Alicia Lozano-Diez:
Bayesian Strategies for Likelihood Ratio Computation in Forensic Voice Comparison with Automatic Systems. CoRR abs/1909.08315 (2019) - 2018
- [c1]Juan Maroñas Molano
Generative Models for Deep Learning with Very Scarce Data. CIARP 2018: 20-28 - 2016
- [i1]Juan Maroñas Molano, Alberto Albiol Colomer, Roberto Paredes Palacios:
Adversarial Ladder Networks. CoRR abs/1611.02320 (2016)
Coauthor Index
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