Publications associées à Convolution on the n-Sphere With Application to PDF Modeling

An Approach for Imitation Learning on Riemannian Manifolds

In imitation learning, multivariate Gaussians are widely used to encode robot behaviors. Such approaches do not provide the ability to properly represent end-effector orientation, as the distance metric in the space of orientations is not Euclidean. In thi ...

2017

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

Rudolf Haraksim

This study presents a method for computing likelihood ratios (LRs) from multimodal score distributions, as the ones produced by some commercial off-the-shelf automated fingerprint identification systems (AFISs). The AFIS algorithms used to compare fingerma ...

Inst Engineering Technology-IET2017

Localization Genus

Jérôme Scherer

Which spaces look like an n-sphere through the eyes of the n-th Postnikov section functor and the n-connected cover functor? The answer is what we call the Postnikov genus of the n-sphere. We define in fact the notion of localization genus for any homotopi ...

Univ Autonoma Barcelona2017

Stability of stationary wave maps from a curved background to a sphere

Sohrab Mirshams Shahshahani

We study time and space equivariant wave maps from

M \times \mathbb{R} \rightarrow S^2

, where

M

is dieomorphic to a two dimensional sphere and admits an action of

SO(2)

by isometries. We assume that metric on

M

can be written as $dr^2+f^2(r)d\theta ...

2016

Flexibeam: Analytic Spatial Filtering By Beamforming

Paul Hurley, Matthieu Martin Jean-André Simeoni

We propose a new, general, method for spatial filtering by beam-forming. The desired filter, specified analytically on an n-dimensional sphere, is extended to n+1-dimensional Euclidean space. A continuous beamforming function is then obtained by the n+1-di ...

Ieee2016

Fast Estimation of Plant Steady State, with Application to Static RTO

Dominique Bonvin, Julien Léo Billeter, Michael Amrhein, Diogo Filipe Mateus Rodrigues

Experimental assessment or prediction of plant steady state is important for many applications in the area of modeling and operation of continuous processes. For example, the iterative implementation of static real-time optimization requires reaching stead ...

2016

Interactive Design of Probability Density Functions for Shape Grammars

Mark Pauly, Duygu Ceylan, Boris Neubert, Stefan Lienhard

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (p ...

Assoc Computing Machinery2015

A Probabilistic Kernel Method for Human Mobility Prediction with Smartphones

Daniel Gatica-Perez

Human mobility prediction is an important problem which has a large num- ber of applications, especially in context-aware services. This paper presents a study on location prediction using smartphone data, in which we address mod- eling and application asp ...

2015

Full blow-up range for co-rotaional wave maps to surfaces of revolution

Can Gao

We construct blow-up solutions of the energy critical wave map equation on

\mathbb{R}^{2+1}\to \mathcal N

with polynomial blow-up rate (

t^{-1-\nu}

for blow-up at

t=0

) in the case when

\mathcal N

is a surface of revolution. Here we extend the blow-u ...

2014

MMSE Estimation of Sparse Levy Processes

Michaël Unser, Arash Amini, Ulugbek Kamilov, Pedram Pad

We investigate a stochastic signal-processing framework for signals with sparse derivatives, where the samples of a Levy process are corrupted by noise. The proposed signal model covers the well-known Brownian motion and piecewise-constant Poisson process; ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Convolution on the n-Sphere With Application to PDF Modeling

Graph Chatbot

Chattez avec Graph Search

An Approach for Imitation Learning on Riemannian Manifolds

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

Localization Genus

Stability of stationary wave maps from a curved background to a sphere

Flexibeam: Analytic Spatial Filtering By Beamforming

Fast Estimation of Plant Steady State, with Application to Static RTO

Interactive Design of Probability Density Functions for Shape Grammars

A Probabilistic Kernel Method for Human Mobility Prediction with Smartphones

Full blow-up range for co-rotaional wave maps to surfaces of revolution

MMSE Estimation of Sparse Levy Processes

Flexibeam: Analytic Spatial Filtering By Beamforming

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

An Approach for Imitation Learning on Riemannian Manifolds

Interactive Design of Probability Density Functions for Shape Grammars

MMSE Estimation of Sparse Levy Processes

A Probabilistic Kernel Method for Human Mobility Prediction with Smartphones

Localization Genus

Stability of stationary wave maps from a curved background to a sphere

Fast Estimation of Plant Steady State, with Application to Static RTO

Full blow-up range for co-rotaional wave maps to surfaces of revolution