104 citations · 124 across the 2 of their papers we have counts for
2 papers
stat.ML2017★ 104 cited
Perspective: Energy Landscapes for Machine Learning
Andrew J. Ballard, Ritankar Das, Stefano Martiniani +4
Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple soluti…
cond-mat.stat-mech2014★ 20 cited
Communication: Newton homotopies for sampling stationary points of potential energy landscapes
Dhagash Mehta, Tianran Chen, Jonathan D Hauenstein +1
One of the most challenging and frequently arising problems in many areas of science is to find solutions of a system of multivariate nonlinear equations. There are several numeric…