3 papers
physics.chem-ph2018
A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians
Haichen Li, Christopher Collins, Matteus Tanha +2
Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an…
physics.chem-ph2015
Embedding parameters in ab initio theory to develop approximations based on molecular similarity
Matteus Tanha, Haichen Li, Shiva Kaul +3
A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is explored, in which parameters are embedded into a low-cost, low-…
physics.chem-ph2013
Embedding parameters in ab initio theory to develop well-controlled approximations based on molecular similarity
Matteus Tanha, Shiva Kaul, Alex Cappiello +2
A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is proposed, in which parameters are embedded into a low-cost, low-…