Name
Abstract | ||
|---|---|---|
We introduce multiscale invariant dictionaries to estimate quantum chemical energies of organic molecules from training databases. Molecular energies are invariant to isometric atomic displacements and are Lipschitz continuous to molecular deformations. Similarly to density functional theory (DFT), the molecule is represented by an electronic density function. A multi scale invariant dictionary is calculated with wavelet scattering invariants. It cascades a first wavelet transform which separates scales with a second wavelet transform which computes interactions across scales. Sparse scattering regressions give state-of-the-art results over two databases of organic planar molecules. On these databases, the regression error is of the order of the error produced by DFT codes, but at a fraction of the computational cost. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1137/16M1075454 | MULTISCALE MODELING & SIMULATION |
Keywords | Field | DocType |
wavelet,scattering,multiscale,nonlinear regression,invariant dictionary,molecular energy,density functional theory,convolutional network | Quantum,Mathematical analysis,Electronic density,Lipschitz continuity,Invariant (mathematics),Density functional theory,Scattering,Mathematics,Wavelet,Wavelet transform | Journal |
Volume | Issue | ISSN |
15 | 2 | 1540-3459 |
Citations | PageRank | References |
7 | 0.71 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew J. Hirn | 1 | 33 | 6.48 |
| Stéphane Mallat | 2 | 4107 | 718.30 |
| Nicolas Poilvert | 3 | 8 | 1.12 |