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We present a sampling-free approach for computing the epistemic uncertainty of a neural network.
On the exact variance of products
L. A. Goodman · 1960
Earlier work this paper cites.
Mixture density networks
C. M. Bishop · 1994
Earlier work this paper cites.
An introduction to the bootstrap
B. Efron and R. J. Tibshirani · 1994
Earlier work this paper cites.
Introduction to error analysis, the study of uncertainties in physical measurements
J. Taylor · 1997
Earlier work this paper cites.
Semantic object classes in video: A high-definition ground truth database
G. J. Brostow, J. Fauqueur, and R. Cipolla · 2009
Earlier work this paper cites.
Practical bayesian optimization of machine learning algorithms
J. Snoek, H. Larochelle, and R. P. Adams · 2012
Earlier work this paper cites.
Vision meets robotics: The kitti dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
Earlier work this paper cites.
Fast dropout training
S. Wang and C. Manning · 2013
Earlier work this paper cites.
Weight uncertainty in neural network
C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra · 2015
Earlier work this paper cites.
Probabilistic backpropagation for scalable learning of bayesian neural networks
J. M. Hernández-Lobato and R. Adams · 2015
Earlier work this paper cites.
A. Kendall, V. Badrinarayanan, and R. Cipolla · 2015
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Uncertainty in deep learning
Y. Gal · 2016
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Y. Gal and Z. Ghahramani · 2016
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Semantic segmentation of small objects and modeling of uncertainty in urban remote sensing images using deep convolutional neural networks
M. Kampffmeyer, A.-B. Salberg, and R. Jenssen · 2016
Cited alongside, same era.
Deep exploration via bootstrapped dqn
I. Osband, C. Blundell, A. Pritzel, and B. Van Roy · 2016
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Natural-parameter networks: A class of probabilistic neural networks
Long-term on-board prediction of people in traffic scenes under uncertainty
A. Bhattacharyya, M. Fritz, and B. Schiele · 2018
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Uncertainty-aware learning from demonstration using mixture density networks with sampling-free variance modeling
S. Choi, K. Lee, S. Lim, and S. Oh · 2018
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Towards safe autonomous driving: Capture uncertainty in the deep neural network for lidar 3d vehicle detection
D. Feng, L. Rosenbaum, and K. Dietmayer · 2018
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Efficient uncertainty estimation for semantic segmentation in videos
P.-Y. Huang, W.-T. Hsu, C.-Y. Chiu, T.-F. Wu, and M. Sun · 2018
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Sampling-free uncertainty estimation in gated recurrent units with exponential families
S. J. Hwang, R. Mehta, and V. Singh · 2018
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Deep bayesian active learning with image data
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Unsupervised monocular depth estimation with left-right consistency
C. Godard, O. Mac Aodha, and G. J. Brostow · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
B. Lakshminarayanan, A. Pritzel, and C. Blundell · 2017
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Learning in an uncertain world: Representing ambiguity through multiple hypotheses
C. Rupprecht, I. Laina, R. DiPietro, M. Baust, F. Tombari, N. Navab, and G. D. Hager · 2017
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Uncertainty estimation for deep neural object detectors in safety-critical applications
M. T. Le, F. Diehl, T. Brunner, and A. Knol · 2018
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Inhibited softmax for uncertainty estimation in neural networks
M. Możejko, M. Susik, and R. Karczewski · 2018
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Bayesian uncertainty estimation for batch normalized deep networks
M. Teye, H. Azizpour, and K. Smith · 2018
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Noisy natural gradient as variational inference
G. Zhang, S. Sun, D. Duvenaud, and R. Grosse · 2018
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