AI meets chemistry: new model predicts molecular Hessian matrices directly, skipping costly derivatives, 10-70 times faster
A University of Toronto team has published a new method, HIP, in Nature Computational Science that directly predicts a molecule's full Hessian matrix, skipping the costly differentiation step.