Fetching the paper…
Reading the bibliography…
We show that training a deep network using batch normalization is equivalent to approximate inference in Bayesian models.
A practical bayesian framework for backpropagation networks
MacKay, D. J · 1992
Earlier work this paper cites.
A practical bayesian framework for backpropagation networks
MacKay, D. J · 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.
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.
Bayesian Learning for Neural Networks
Neal, R. M · 1995
Earlier work this paper cites.
Delve Datasets
Ghahramani, Z · 1996
Earlier work this paper cites.
Delve Datasets
Ghahramani, Z · 1996
Earlier work this paper cites.
Axiomatic characterization of the quadratic scoring rule
Selten, R · 1998
Earlier work this paper cites.
Axiomatic characterization of the quadratic scoring rule
Selten, R · 1998
Earlier work this paper cites.
Elements of Large-Sample Theory
Lehmann, E. L · 1999
Earlier work this paper cites.
Elements of Large-Sample Theory
Lehmann, E. L · 1999
Earlier work this paper cites.
Strictly Proper Scoring Rules, Prediction, and Estimation
Gneiting, T. and Raftery, A. E · 2007
Earlier work this paper cites.
Strictly Proper Scoring Rules, Prediction, and Estimation
Gneiting, T. and Raftery, A. E · 2007
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Krizhevsky, A. and Hinton, G · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Krizhevsky, A. and Hinton, G · 2009
Earlier work this paper cites.
Practical Variational Inference for Neural Networks
Graves, A · 2011
Earlier work this paper cites.
Practical Variational Inference for Neural Networks
Graves, A · 2011
Earlier work this paper cites.
Bayesian learning for neural networks , volume 118
Neal, R. M · 2012
Earlier work this paper cites.
Bayesian learning for neural networks , volume 118
Neal, R. M · 2012
Earlier work this paper cites.
Fast dropout training
Wang, S. I. and Manning, C. D · 2013
Cited alongside, same era.
Fast dropout training
Wang, S. I. and Manning, C. D · 2013
Cited alongside, same era.
Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C · 2014
Cited alongside, same era.
Auto-Encoding Variational Bayes
Kingma, D. P. and Welling, M · 2014
Cited alongside, same era.
Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C · 2014
Cited alongside, same era.
Auto-Encoding Variational Bayes
Kingma, D. P. and Welling, M · 2014
Cited alongside, same era.
Uncertainty in Deep Learning
Gal, Y · 2016
Later among the works it cites.
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Bui, T. D., Hernández-Lobato, D., Li, Y., Hernández-Lobato, J. M., and Turner, R. E · 2016
Later among the works it cites.
Monocular 3d object detection for autonomous driving
Chen, X., Kundu, K., Zhang, Z., Ma, H., Fidler, S., and Urtasun, R · 2016
Later among the works it cites.
Uncertainty in Deep Learning
Gal, Y · 2016
Later among the works it cites.
Precision histology: how deep learning is poised to revitalize histomorphology for personalized cancer care
Djuric, U., Zadeh, G., Aldape, K., and Diamandis, P · 2017
Later among the works it cites.
Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., and Thrun, S · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dropout as a Bayesian Approximation : Representing Model Uncertainty in Deep Learning
Gal, Y. and Ghahramani, Z · 2015
Cited alongside, same era.
Probabilistic machine learning and artificial intelligence
Ghahramani, Z · 2015
Cited alongside, same era.
Probabilistic backpropagation for scalable learning of bayesian neural networks
Hernández-Lobato, J. M. and Adams, R · 2015
Cited alongside, same era.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Ioffe, S. and Szegedy, C · 2015
Cited alongside, same era.
Convnetjs demo: toy 1d regression, 2015
Karpathy, A · 2015
Cited alongside, same era.
Kendall, A., Badrinarayanan, V., and Cipolla, R · 2015
Cited alongside, same era.
Later among the works it cites.
Batch renormalization: Towards reducing minibatch dependence in batch-normalized models
Ioffe, S · 2017
Later among the works it cites.
Krueger, D., Huang, C.-W., Islam, R., Turner, R., Lacoste, A., and Courville, A · 2017
Later among the works it cites.
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Li, Y. and Gal, Y · 2017
Later among the works it cites.
Multiplicative normalizing flows for variational Bayesian neural networks
Louizos, C. and Welling, M · 2017
Later among the works it cites.
End-to-end training for whole image breast cancer diagnosis using an all convolutional design
Shen, L · 2017
Later among the works it cites.
UC Irvine Machine Learning Repository, 2017
University of California, I · 2017
Later among the works it cites.
Precision histology: how deep learning is poised to revitalize histomorphology for personalized cancer care
Djuric, U., Zadeh, G., Aldape, K., and Diamandis, P · 2017
Later among the works it cites.
Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., and Thrun, S · 2017
Later among the works it cites.
Batch renormalization: Towards reducing minibatch dependence in batch-normalized models
Ioffe, S · 2017
Later among the works it cites.
Krueger, D., Huang, C.-W., Islam, R., Turner, R., Lacoste, A., and Courville, A · 2017
Later among the works it cites.
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Li, Y. and Gal, Y · 2017
Later among the works it cites.
Multiplicative normalizing flows for variational Bayesian neural networks
Louizos, C. and Welling, M · 2017
Later among the works it cites.
End-to-end training for whole image breast cancer diagnosis using an all convolutional design
Shen, L · 2017
Later among the works it cites.
UC Irvine Machine Learning Repository, 2017
University of California, I · 2017
Later among the works it cites.