Vincent Maillot

Formes automorphes et theoremes de Riemann-Roch arithmetiques (2008)

Maillot, Vincent, Rössler, Damian

Nous construisons trois familles de formes automorphes au moyen du theoreme de Riemann-Roch arithmetique et de la formule de Lefschetz arithmetique. Deux de ces familles ont deja ete construites par...

On the determinant bundles of abelian schemes (2006)

Maillot, Vincent, Rössler, Damian

Let $\pi:\CA\ra S$ be an abelian scheme over a scheme $S$ which is quasi-projective over an affine noetherian scheme and let $\CL$ be a symmetric, rigidified, relatively ample line bundle on $\CA$....

On the periods of motives with complex multiplication and a conjecture of Gross-Deligne (2004)

Maillot, Vincent, Roessler, Damian

We prove that the existence of an automorphism of finite order on a $\Qb$-variety $X$ implies the existence of algebraic linear relations between the logarithm of certain periods of $X$ and the...

Conjectures sur les d\'eriv\'ees logarithmiques des fonctions L d'Artin aux entiers n\'egatifs (2002)

Maillot, Vincent, Roessler, Damien

We formulate several variants of a conjecture relating the arithmetic degree of certain hermitian fibre bundles with the values of the logarithmic derivative of Artin's L-functions at negative...

Uniqueness Of Weights For Neural Networks (1993)

Francesca Albertini, Eduardo D. Sontag, Vincent Maillot

Introduction In most applications dealing with learning and pattern recognition, neural nets are employed as models whose parameters, or "weights," must be fit to training data. Gradient...

Uniqueness Of Weights For Neural Networks (1993)

Francesca Albertini, Eduardo D. Sontag, Vincent Maillot

Introduction In most applications dealing with learning and pattern recognition, neural nets are employed as models whose parameters, or "weights," must be fit to training data. Gradient...

Uniqueness of weights for neural networks (1993)

Francesca Albertini, Eduardo D. Sontag, Vincent Maillot

In most applications dealing with learning and pattern recognition, neural nets are employed as models whose parameters, or “weights, ” must be fit to training data. Gradient descent and other...