MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes

16 April 2018

Papers citing "MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes"

7 / 7 papers shown

Title
Nonlinearity Enhanced Adaptive Activation Functions David Yevick 65 1 0 29 Mar 2024
Regularisation of Neural Networks by Enforcing Lipschitz Continuity Henry Gouk E. Frank Bernhard Pfahringer M. Cree 170 478 0 12 Apr 2018
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 179 592 0 22 May 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 207 9,548 0 31 Mar 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 339 4,629 0 10 Nov 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 340 7,985 0 23 May 2016
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 226 1,514 0 08 Jun 2015