Curvature-based Comparison of Two Neural Networks

J.M. Lee, Riemannian Manifolds . Springer, New York, 1997

1997

Earlier work this paper cites.

P. Petersen, Riemann Geometry . Springer, New York, 1998

1998

Earlier work this paper cites.

Van Dyk, D.A. and Meng, X.L. The art of data augmentation . Journal of Computational and Graphical Statistics, 10(1), pp.1-50, 2001

2001

Earlier work this paper cites.

Lee, John M, Introduction to Smooth Manifolds . Springer-Verlag, New York, 2nd, 2003

2003

Earlier work this paper cites.

Behzad Eftekhar, Kazem Mohammad, Hassan Eftekhar Ardebili, Mohammad Ghodsi, and Ebrahim Ketabchi, Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data . BMC Med. Inf. & Decision Making 5: 3, 2005

2005

Earlier work this paper cites.

Jianzhong Wang, Geometric structure of high-dimensional data and dimensionality reduction . Springer-Verlag, New York, 2nd, 2011

2011

Earlier work this paper cites.

S. Rifai, Y. N. Dauphin, P. Vincent, Y. Bengio, and X. Muller. The manifold tangent classifier . In NIPS, pp.2294�C2302, 2011

2011

Cited alongside, same era.

Krizhevsky Alex, Sutskever Ilya, Hinton Geoffrey E, Imagenet classification with deep convolutional neural networks . NIPS 2012, 1097–1105, 2012

2012

Cited alongside, same era.

Brahma, Pratik Prabhanjan, Wu Dapeng, She Yiyuan, Why deep learning works: A manifold disentanglement perspective . IEEE transactions on neural networks and learning systems, 27(10), 1997-2008, 2016

2016

Cited alongside, same era.

C. K. Chui and H. N. Mhaskar. Deep nets for local manifold learning . ArXiv preprint:1607.07110, 2016

2016

Cited alongside, same era.

Y. Li, J. Yosinski, J. Clune, H. Lipson, and J. Hopcroft. Convergent Learning: Do different neural networks learn the same representations? In International Conference on Learning Representations (ICLR), May 2016

Avrim Blum, John Hopcroft, and Ravindran Kannan, Foundations of Data Science . https://www.cs.cornell.edu/jeh/book.pdf

2017

Later among the works it cites.

Wang, Jason, and Luis Perez, The Effectiveness of Data Augmentation in Image Classification using Deep Learning . Technical report, Stanford University, 2017

2017

Later among the works it cites.

Yangyang Li, Curvature-aware Manifold Learning . CoRR abs/1706.07167, 2017

Original

2017

Later among the works it cites.

Sze, Vivienne and Chen, Yu-Hsin and Yang, Tien-Ju and Emer, Joel, Efficient processing of deep neural networks: A tutorial and survey . arXiv preprint arXiv:1703.09039, 2017

Original

2017

Later among the works it cites.

W Liu, Z Wang, X Liu, N Zeng, Y Liu, FE Alsaadi, A survey of deep neural network architectures and their applications . Neurocomputing, 2017