19 citations · 41 across the 6 of their papers we have counts for
Showing 2017Show all
3 papers · 1 filter
cs.NE2017★ 11 cited
Neural networks catching up with finite differences in solving partial differential equations in higher dimensions
V. I. Avrutskiy
Fully connected multilayer perceptrons are used for obtaining numerical solutions of partial differential equations in various dimensions. Independent variables are fed into the in…
cs.NE2017★ 6 cited
Backpropagation generalized for output derivatives
V. I. Avrutskiy
Backpropagation algorithm is the cornerstone for neural network analysis. Paper extends it for training any derivatives of neural network's output with respect to its input. By the…
cs.NE2017★ 19 cited
Enhancing approximation abilities of neural networks by training derivatives
V. I. Avrutskiy
A method to increase the precision of feedforward networks is proposed. It requires a prior knowledge of a target function derivatives of several orders and uses this information i…