DCR_data.mat

In summary, the DCR (Direct Current Resistivity) dataset detects an object from indirect noisy measurements under a general mathematical formulation that is similar in nature to a problem that arises in modeling porous media flow with Darcy's Law. Haley Rosso is the principle point of contact for the affiliated paper, "Weight-Parameterization in Continuous TimeDeep Neural Networks for Surrogate Modeling". Lars Ruthotto (co-author) is the creator of this dataset, which we pulled from his github repository entitled "Meganet.m". This data upload serves to reproduce the experiments performed in the paper. The paper is also co-authored by Khachik Sargsyan of Sandia National Labs, who oversaw the writing of the paper and provided data for the "ELM" experiment in the paper, the data for which can be found in the paper's github repo "Continuous_DNN_Surrogates_Revised".