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Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Publications associées (39)

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We applied density functional theory based on ultrasoft pseudopotentials to study the structural properties of Ir-4 clusters both in the gas phase and adsorbed on a MgO(100) surface. To resolve the discrepancy between experimental data which suggest a tetr ...

2010

In a posteriori error analysis of reduced basis approximations to affinely parametrized partial differential equations, the construction of lower bounds for the coercivity and inf-sup stability constants is essential. In [Huynh et al., C. R. Acad. Sci. Par ...

EDP SCIENCES S A2009

Composite Kernel Learning

The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning (MKL) enables to learn the kernel, from an ensemble of ...

Omnipress2008

IDIAP2008

Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear ...

2008

Increasing awareness that popular functionals fail to describe many energies accurately has ended expectations of black-box DFT usage. The performance of nine d. functionals, compared by computing the bond sepn. energies of 72 illustrative hydrocarbons wit ...

2007

We show that for a voter model on {0,1}Z corresponding to a random walk with kernel p(·) and starting from unanimity to the right and opposing unanimity to the left, a tight interface between 0's and 1's exists if p(·) has second moments but does not if p( ...

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Using a first-principles approach, we assign N 1s core-level shifts at ammonium exposed Si(001)2x1 surfaces to definite bonding configurations of N atoms. Model structures are obtained by fully relaxing the atomic positions of N atoms in different bonding ...

2000

Radiative transfer is often the dominant energy transport channel in inertial confinement fusion experiments. It is a basic process needed in order to understand the behaviour of astrophysical plasmas, like stellar atmospheres and the inner parts of stars. ...

EPFL1994