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Gradient Regularization Improves Accuracy of Discriminative Models

Varga Dániel, Csiszárik Adrián, Zombori Zsolt

Schedae Informaticae

2018

Vol. 27

31--45

Regularizing the gradient norm of the output of a neural network is a powerful technique, rediscovered several times. This paper presents evidence that gradient regularization can consistently improve classification accuracy on vision tasks, using modern deep neural networks, especially when the amount of training data is small. We introduce our regularizers as members of a broader class of Jacobian-based regularizers. We demonstrate empirically on real and synthetic data that the learning process leads to gradients controlled beyond the training points, and results in solutions that generalize well.

Imperfection sensitivity of shear banding in gradient-dependent Cam-clay plasticity model

Stankiewicz A.

Computer Assisted Methods in Engineering and Science

2015

Vol. 22, no. 2

115--139

The paper deals with the numerical simulation of strain localization in granular two-phase material. A gradient enhancement of modified Cam-clay model is introduced to overcome the problem of spurious discretization sensitivity of finite element solution. Two- and three-field finite elements implemented in the finite element analysis program (FEAP) are used in numerical simulations. The attention is focused on imperfection sensitivity of shear banding simulations. An application of the modelling framework to the slope stability problem is also included.

Finite element analysis of fluid influence on instabilities in two-phase Cam-clay plasticity model

Stankiewicz A., Pamin J.

Computer Assisted Mechanics and Engineering Sciences

2006

Vol. 13, No. 4

669-682

The influence of fluid phase on soil instabilities is investigated using the modified Cam-clay model within a two-phase description. Spurious mesh dependence of finite element results is prevented by a gradient enhancement of the model. The results of numerical tests for one-phase and two-phase model are compared. The influence of permeability on the stabilizing role of the fluid phase is assessed.