Artículo Cientifico "Clustering of vety low energy particles"CARMEN IGLESIAS
This note compares different ways of reconstructing the clusters inside the ATHENA framework of ATLAS: Topocluster, Sliding Window Cluster, EGamma Cluster and cone algorithms. We show how these clustering algorithms can be turned to obtain the best energy resolution when reconstructing very low energy particles. The present results are based on single particle samples of pi0's, pi+'s, and neutrons, simulated with Geant3 during DC1 with energy between 1 and 30 GeV and simulated with and without electronic noise in the calorimeters. Results in this note are obtained using 7.8.0 and 8.2.0 releases of the ATLAS software.
Goman, Khrabrov, Khramtsovsky (2002) - Chaotic dynamics in a simple aeromecha...Project KRIT
М.Г.Гоман, А.Н.Храмбров. А.В.Храмцовский «Хаотическая динамика простой аэромеханической системы», глава в книге под ред. Дж.Блэклиджа, А.Иванса и М.Тернера «Фрактальная геометрия: Математические методы. алгоритмы, приложения» (Fractal Geometry: Mathematical Methods, Algorithms, Applications), Horwood Publishing, 2002 г.
M.G.Goman, A.N.Khrabrov, A.V.Khramtsovsky "Chaotic dynamics in a simple aeromechanical system", chapter in a book: J.Blackledge, A.Evans, and M.Turner (eds.), "Fractal Geometry: Mathematical Methods, Algorithms, Applications", Horwood Publishing Series in Mathematics and Applications, 2002.
Dynamics of a free-to-roll delta wing installed at high incidence in a wind tunnel is outlined using the experimental and mathematical modeling results. A simple analytical model applied allows to simulate the multiattractor and chaotic dynamics observed in wind tunnel tests and thus to validate the used method for nonlinear and unsteady aerodynamics loads representation.
Patch Matching with Polynomial Exponential Families and Projective DivergencesFrank Nielsen
This document presents a method called Polynomial Exponential Family-Patch Matching (PEF-PM) to solve the patch matching problem. PEF-PM models patch colors using polynomial exponential families (PEFs), which are universal smooth positive densities. It estimates PEFs using a Score Matching Estimator and accelerates batch estimation using Summed Area Tables. Patch similarity is measured using a statistical projective divergence called the symmetrized γ-divergence. Experiments show PEF-PM handles noise robustly, symmetries, and outperforms baseline methods.
On representing spherical videos (Frank Nielsen, CVPR 2001)Frank Nielsen
The document discusses different geometric shapes like cubes, dodecahedrons, and icosahedrons that can be used as envelopes. It also mentions that images can be interactively slid onto these envelopes and spherical maps can be generated using techniques like Buckyballer's unfolded icosahedron map or stratified random and Hammersley sequences.
Artículo Cientifico "Clustering of vety low energy particles"CARMEN IGLESIAS
This note compares different ways of reconstructing the clusters inside the ATHENA framework of ATLAS: Topocluster, Sliding Window Cluster, EGamma Cluster and cone algorithms. We show how these clustering algorithms can be turned to obtain the best energy resolution when reconstructing very low energy particles. The present results are based on single particle samples of pi0's, pi+'s, and neutrons, simulated with Geant3 during DC1 with energy between 1 and 30 GeV and simulated with and without electronic noise in the calorimeters. Results in this note are obtained using 7.8.0 and 8.2.0 releases of the ATLAS software.
Goman, Khrabrov, Khramtsovsky (2002) - Chaotic dynamics in a simple aeromecha...Project KRIT
М.Г.Гоман, А.Н.Храмбров. А.В.Храмцовский «Хаотическая динамика простой аэромеханической системы», глава в книге под ред. Дж.Блэклиджа, А.Иванса и М.Тернера «Фрактальная геометрия: Математические методы. алгоритмы, приложения» (Fractal Geometry: Mathematical Methods, Algorithms, Applications), Horwood Publishing, 2002 г.
M.G.Goman, A.N.Khrabrov, A.V.Khramtsovsky "Chaotic dynamics in a simple aeromechanical system", chapter in a book: J.Blackledge, A.Evans, and M.Turner (eds.), "Fractal Geometry: Mathematical Methods, Algorithms, Applications", Horwood Publishing Series in Mathematics and Applications, 2002.
Dynamics of a free-to-roll delta wing installed at high incidence in a wind tunnel is outlined using the experimental and mathematical modeling results. A simple analytical model applied allows to simulate the multiattractor and chaotic dynamics observed in wind tunnel tests and thus to validate the used method for nonlinear and unsteady aerodynamics loads representation.
Patch Matching with Polynomial Exponential Families and Projective DivergencesFrank Nielsen
This document presents a method called Polynomial Exponential Family-Patch Matching (PEF-PM) to solve the patch matching problem. PEF-PM models patch colors using polynomial exponential families (PEFs), which are universal smooth positive densities. It estimates PEFs using a Score Matching Estimator and accelerates batch estimation using Summed Area Tables. Patch similarity is measured using a statistical projective divergence called the symmetrized γ-divergence. Experiments show PEF-PM handles noise robustly, symmetries, and outperforms baseline methods.
On representing spherical videos (Frank Nielsen, CVPR 2001)Frank Nielsen
The document discusses different geometric shapes like cubes, dodecahedrons, and icosahedrons that can be used as envelopes. It also mentions that images can be interactively slid onto these envelopes and spherical maps can be generated using techniques like Buckyballer's unfolded icosahedron map or stratified random and Hammersley sequences.
The dual geometry of Shannon informationFrank Nielsen
The document discusses the dual geometry of Shannon information. It covers:
1. Shannon entropy and related concepts like maximum entropy principle and exponential families.
2. The properties of Kullback-Leibler divergence including its interpretation as a statistical distance and relation to maximum entropy.
3. How maximum likelihood estimation for exponential families can be viewed as minimizing Kullback-Leibler divergence between the empirical distribution and model distribution.
Computational Information Geometry: A quick review (ICMS)Frank Nielsen
From the workshop
Computational information geometry for image and signal processing
Sep 21, 2015 - Sep 25, 2015
ICMS, 15 South College Street, Edinburgh
http://www.icms.org.uk/workshop.php?id=343
Classification with mixtures of curved Mahalanobis metricsFrank Nielsen
This document discusses curved Mahalanobis distances in Cayley-Klein geometries and their application to classification. Specifically:
1. It introduces Mahalanobis distances and generalizes them to curved distances in Cayley-Klein geometries, which can model both elliptic and hyperbolic geometries.
2. It describes how to learn these curved Mahalanobis metrics using an adaptation of Large Margin Nearest Neighbors (LMNN) to the elliptic and hyperbolic cases.
3. Experimental results on several datasets show that curved Mahalanobis distances can achieve comparable or better classification accuracy than standard Mahalanobis distances.
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