Publications related to A structured prediction approach for robot imitation learning

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Sobolev inequalities for differential forms and $L_{q,p}$-cohomology

Marc Troyanov

We study the relation between Sobolev inequalities for differential forms on a Riemannian manifold

(M,g)

and the

L_{q,p}

-cohomology of that manifold. The

L_{q,p}

-cohomology of

(M,g)

is defined to be the quotient of the space of closed differential ...

2006

A structured prediction approach for robot imitation learning

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$L_{q,p}$-cohomology of Riemannian Manifolds with Negative Curvature

Product groups acting on manifolds

Diffusion Spectrum Imaging Shows the Structural Basis of Functional Cerebellar Circuits in the Human Cerebellum In Vivo

Predicting the Dominant Clique in Meetings through Fusion of Nonverbal Cues

Using Comparison of Parallel Phoneme Probability streams for OOV Word Detection

Predicting the dominant clique in meetings through fusion of nonverbal cues

Some applications of symmetries in differential geometry and dynamical systems

Optimal control of geodesics in Riemannian manifolds

Generation of Various Complex Patterned Structures From a Single Ellipsoidal Dot Prepattern by Capillary Force Lithography

Sobolev inequalities for differential forms and $L_{q,p}$-cohomology

Product groups acting on manifolds

Optimal control of geodesics in Riemannian manifolds

Predicting the dominant clique in meetings through fusion of nonverbal cues

Using Comparison of Parallel Phoneme Probability streams for OOV Word Detection

Diffusion Spectrum Imaging Shows the Structural Basis of Functional Cerebellar Circuits in the Human Cerebellum In Vivo

Sobolev inequalities for differential forms and $L_{q,p}$-cohomology

$L_{q,p}$-cohomology of Riemannian Manifolds with Negative Curvature

Some applications of symmetries in differential geometry and dynamical systems

Predicting the Dominant Clique in Meetings through Fusion of Nonverbal Cues

Generation of Various Complex Patterned Structures From a Single Ellipsoidal Dot Prepattern by Capillary Force Lithography