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Among the various options to estimate uncertainty in deep neural networks, Monte-Carlo dropout is widely popular for its simplicity and effectiveness.
Transforming Neural-net Output Levels to Probability Distributions
Denker, J. S. and LeCun, Y · 1990
Earlier work this paper cites.
A Practical Bayesian Framework for Backpropagation Networks
MacKay, D. J. C · 1992
Earlier work this paper cites.
Weight Uncertainty in Neural Network
Blundell, C., Cornebise, J., Kavukcuoglu, K., and Wierstra, D · 2015
Earlier work this paper cites.
Dropout As a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Gal, Y. and Ghahramani, Z · 2016
Earlier work this paper cites.
Modelling uncertainty in deep learning for camera relocalization
Kendall, A. and Cipolla, R · 2016
Earlier work this paper cites.
Risk versus Uncertainty in Deep Learning: Bayes, Bootstrap and the Dangers of Dropout
Osband, I · 2016
Earlier work this paper cites.
Deep Exploration via Bootstrapped DQN
Osband, I., Blundell, C., Pritzel, A., and Van Roy, B · 2016
Cited alongside, same era.
Concrete Dropout
Gal, Y., Hron, J., and Kendall, A · 2017
Cited alongside, same era.
Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding
Kendall, A., Badrinarayanan, V., and Cipolla, R · 2017
Cited alongside, same era.
Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction
Jungo, A., McKinley, R., Meier, R., Knecht, U., Vera, L., Pérez-Beteta, J., Molina-García, D., Pérez-García, V. M., Wiest, R., and Reyes, M · 2018
Cited alongside, same era.
Pearce, T., Anastassacos, N., Zaki, M., and Neely, A · 2018
Cited alongside, same era.
Calibrating Uncertainties in Object Localization Task
Phan, B., Salay, R., Czarnecki, K., Abdelzad, V., Denouden, T., and Vernekar, S · 2018
Later among the works it cites.
Deep Network Uncertainty Maps for Indoor Navigation
Verdoja, F., Lundell, J., and Kyrki, V · 2019
Later among the works it cites.
Learnable Bernoulli Dropout for Bayesian Deep Learning
Boluki, S., Ardywibowo, R., Dadaneh, S. Z., Zhou, M., and Qian, X · 2020
Closest in time.
Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms
Caldeira, J. and Nord, B · 2020
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A General Framework for Uncertainty Estimation in Deep Learning
Loquercio, A., Segù, M., and Scaramuzza, D · 2020
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