Robust and Active Learning for Deep Neural Network Regression

no code implementations • 28 Jul 2021 • Xi Li, George Kesidis, David J. Miller, Maxime Bergeron, Ryan Ferguson, Vladimir Lucic

We describe a gradient-based method to discover local error maximizers of a deep neural network (DNN) used for regression, assuming the availability of an "oracle" capable of providing real-valued supervision (a regression target) for samples.

Active Learning regression

Deeply Learning Derivatives

no code implementations • 6 Sep 2018 • Ryan Ferguson, Andrew Green

This paper uses deep learning to value derivatives.