Kelli Humbird

Deep Jointly-Informed neural networks

2018

OJINN Is an easy-to-use deep neural network model that requires fewer user-specified hyper-parameters than traditional neural networks. The algorithm leverages decision trees trained on the data to determine an appropriate deep neural network architectures and …

Deep learning: A guide for practitioners in the physical sciences

2018 · Physics of Plasmas

Machine learning is finding increasingly broad applications in the physical sciences. This most often involves building a model relationship between a dependent, measurable output, and an associated set of controllable, but complicated, independent inputs. We …