Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

On the likelihood that one unknown probability exceeds another in view of the evidence of two samples

Thompson, W R · 1933

Earlier work this paper cites.

A practical Bayesian framework for backpropagation networks

MacKay, D J C · 1992

Earlier work this paper cites.

Keeping the neural networks simple by minimizing the description length of the weights

Hinton, G E and Van Camp, D · 1993

Earlier work this paper cites.

Bayesian learning for neural networks

Neal, R M · 1995

Earlier work this paper cites.

Computing with infinite networks

Original

Williams, C K I · 1997

Earlier work this paper cites.

Ensemble learning in Bayesian neural networks

Barber, D and Bishop, C M · 1998

Earlier work this paper cites.

The mnist database of handwritten digits, 1998

LeCun, Y and Cortes, C · 1998

Earlier work this paper cites.

Gradient-based learning applied to document recognition

LeCun, Y, Bottou, L, Bengio, Y, and Haffner, P · 1998

Earlier work this paper cites.

Atmospheric CO2 concentrations (ppmv) derived from in situ air samples collected at Mauna Loa Observatory, Hawaii, 2004

Keeling, C D, Whorf, T P, and the Carbon Dioxide Research Group · 2004

Earlier work this paper cites.

Solar irradiance reconstruction

Lean, J · 2004

Earlier work this paper cites.

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)

Rasmussen, C E and Williams, C K I · 2006

Earlier work this paper cites.

Neural network based intrusion detection system for critical infrastructures

Linda, O, Vollmer, T, and Manic, M · 2009

Earlier work this paper cites.

Theano: a CPU and GPU math expression compiler

Bergstra, James, Breuleux, Olivier, Bastien, Frédéric, Lamblin, Pascal, Pascanu, Razvan, Desjardins, Guillaume, Turian, Joseph, Warde-Farley, David, and Bengio, Yoshua · 2010

Earlier work this paper cites.

Algorithms for reinforcement learning

Szepesvári, C · 2010

Earlier work this paper cites.

Practical variational inference for neural networks

Graves, A · 2011

Cited alongside, same era.

Variational Bayesian inference with stochastic search

Blei, D M, Jordan, M I, and Paisley, J W · 2012

Cited alongside, same era.

Practical Bayesian optimization of machine learning algorithms

Snoek, Jasper, Larochelle, Hugo, and Adams, Ryan P · 2012

Cited alongside, same era.

Deep Gaussian processes

Damianou, A and Lawrence, N · 2013

Cited alongside, same era.

Experimental biology: Sometimes Bayesian statistics are better

Herzog, S and Ostwald, D · 2013

Cited alongside, same era.

Stochastic variational inference

Hoffman, M D, Blei, D M, Wang, C, and Paisley, J · 2013

Cited alongside, same era.

A Bayesian encourages dropout

Original

Maeda, S · 2014

Later among the works it cites.

Statistical errors

Nuzzo, Regina · 2014

Later among the works it cites.

Stochastic backpropagation and approximate inference in deep generative models

Rezende, D J, Mohamed, S, and Wierstra, D · 2014

Later among the works it cites.

Dropout: A simple way to prevent neural networks from overfitting

Srivastava, N, Hinton, G, Krizhevsky, A, Sutskever, I, and Salakhutdinov, R · 2014

Later among the works it cites.

Doubly stochastic variational Bayes for non-conjugate inference

Titsias, M and Lázaro-Gredilla, M · 2014

Later among the works it cites.

Neural networks applied to discriminate botanical origin of honeys

Anjos, O, Iglesias, C, Peres, F, Martínez, J, García, Á, and Taboada, J · 2015