About: covid:PMC7274324

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An Entity of Type : owl:Thing, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
Creator	Bouchon-Meunier, Bernadette Lesot, Marie-Jeanne Vieira, Susana Yager, Ronald Carvalho, João Falkman, Göran Karlsson, Alexander Mathiason, Gunnar Reformat, Marek Ståhl, Niclas Wilbik, Anna
is schema:about of	named entity 'DEEP LEARNING' named entity 'EVALUATION' named entity 'Bayesian' named entity 'deep learning' named entity 'outlier' named entity 'gradient information' named entity 'training data' named entity 'cross entropy' named entity 'softmax' named entity 'Bayesian' named entity 'neurons' named entity 'neural network' named entity 'loss function' named entity 'softmax' named entity 'Euclidean distance' named entity 'gradient information' named entity 'neural networks' named entity 'softmax' named entity 'epistemic uncertainty' named entity 'decision maker' named entity 'reconstruction error' named entity 'softmax activation function' named entity 'MNIST' named entity 'softmax function' named entity 'softmax function' named entity 'deep neural network' named entity 'probability distribution' named entity 'Euclidean distance' named entity 'heteroscedastic' named entity 'neural network' named entity 'neurons' named entity 'Bayesian' named entity 'posterior distribution' named entity 'MNIST' named entity 'learning algorithms' named entity 'MNIST' named entity 'informed decision' named entity 'neural network' named entity 'uncertainty quantification' named entity 'MNIST' named entity 'training set' named entity 'skin cancer' named entity 'autoencoder' named entity 'overfitting' named entity 'inference' named entity 'neural network' named entity 'MNIST' named entity 'cross entropy' named entity 'probability distribution' named entity 'classifier' named entity 'softmax' named entity 'deep learning' named entity 'training set' named entity 'cross entropy' named entity 'bootstrap samples' named entity 'deep learning' named entity 'feed forward' named entity 'neural networks' named entity 'Neural Networks' named entity 'point estimate' named entity 'neural networks' named entity 'neurons' named entity 'predictive model' named entity 'posterior distribution' named entity 'decision boundaries' named entity 'uncertainty quantification' named entity 'log-likelihood' named entity 'deep neural networks' named entity 'softmax' named entity 'uncertainty quantification' named entity 'autoencoder' named entity 'epistemic uncertainty' named entity 'autoencoder' named entity 'softmax' named entity 'vector' named entity 'epistemic' named entity 'deep learning' named entity 'classifiers' named entity 'epistemic uncertainty' named entity 'uncertainty quantification' named entity 'autoencoder' named entity 'MNIST' named entity 'Bayesian' named entity 'autoencoder' named entity 'Shannon entropy' named entity 'softmax' named entity 'MNIST' named entity 'Bayesian' named entity 'autoencoder'

Attributes

Values

Creator

Bouchon-Meunier, Bernadette
Lesot, Marie-Jeanne
Vieira, Susana
Yager, Ronald
Carvalho, João
Falkman, Göran
Karlsson, Alexander
Mathiason, Gunnar
Reformat, Marek
Ståhl, Niclas
Wilbik, Anna

is schema:about of

named entity 'DEEP LEARNING'
named entity 'EVALUATION'
named entity 'Bayesian'
named entity 'deep learning'
named entity 'outlier'
named entity 'gradient information'
named entity 'training data'
named entity 'cross entropy'
named entity 'softmax'
named entity 'Bayesian'
named entity 'neurons'
named entity 'neural network'
named entity 'loss function'
named entity 'softmax'
named entity 'Euclidean distance'
named entity 'gradient information'
named entity 'neural networks'
named entity 'softmax'
named entity 'epistemic uncertainty'
named entity 'decision maker'
named entity 'reconstruction error'
named entity 'softmax activation function'
named entity 'MNIST'
named entity 'softmax function'
named entity 'softmax function'
named entity 'deep neural network'
named entity 'probability distribution'
named entity 'Euclidean distance'
named entity 'heteroscedastic'
named entity 'neural network'
named entity 'neurons'
named entity 'Bayesian'
named entity 'posterior distribution'
named entity 'MNIST'
named entity 'learning algorithms'
named entity 'MNIST'
named entity 'informed decision'
named entity 'neural network'
named entity 'uncertainty quantification'
named entity 'MNIST'
named entity 'training set'
named entity 'skin cancer'
named entity 'autoencoder'
named entity 'overfitting'
named entity 'inference'
named entity 'neural network'
named entity 'MNIST'
named entity 'cross entropy'
named entity 'probability distribution'
named entity 'classifier'
named entity 'softmax'
named entity 'deep learning'
named entity 'training set'
named entity 'cross entropy'
named entity 'bootstrap samples'
named entity 'deep learning'
named entity 'feed forward'
named entity 'neural networks'
named entity 'Neural Networks'
named entity 'point estimate'
named entity 'neural networks'
named entity 'neurons'
named entity 'predictive model'
named entity 'posterior distribution'
named entity 'decision boundaries'
named entity 'uncertainty quantification'
named entity 'log-likelihood'
named entity 'deep neural networks'
named entity 'softmax'
named entity 'uncertainty quantification'
named entity 'autoencoder'
named entity 'epistemic uncertainty'
named entity 'autoencoder'
named entity 'softmax'
named entity 'vector'
named entity 'epistemic'
named entity 'deep learning'
named entity 'classifiers'
named entity 'epistemic uncertainty'
named entity 'uncertainty quantification'
named entity 'autoencoder'
named entity 'MNIST'
named entity 'Bayesian'
named entity 'autoencoder'
named entity 'Shannon entropy'
named entity 'softmax'
named entity 'MNIST'
named entity 'Bayesian'
named entity 'autoencoder'

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