no code implementations • 21 Nov 2018 • Xavier Brumwell, Paul Sinz, Kwang Jin Kim, Yue Qi, Matthew Hirn
Here this approach is extended for general steerable wavelets which are equivariant to translations and rotations, resulting in a sparse model of the target function.
no code implementations • 1 Jun 2020 • Paul Sinz, Michael W. Swift, Xavier Brumwell, Jialin Liu, Kwang Jin Kim, Yue Qi, Matthew Hirn
The dream of machine learning in materials science is for a model to learn the underlying physics of an atomic system, allowing it to move beyond interpolation of the training set to the prediction of properties that were not present in the original training data.