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In the article arXiv:1108.5443 we established a general group-theoretical approach to the construction of B\"acklund transformations. We then showed how this construction can be applied to construct B\"acklund transformation between…

Differential Geometry · Mathematics 2015-09-03 Ian M. Anderson , Mark E. Fels

At its core, abstraction is the process of generalizing from specific instances to broader concepts or models, with the primary objective of reducing complexity while preserving properties essential to the intended purpose. It is…

Logic in Computer Science · Computer Science 2026-01-06 Andrzej Szalas

We introduce and study on examples a notion of the Artin shape for a motive related to a projective homogenous variety. We apply it to the problem of finding the complete motivic decomposition of the variety. Our examples cover unitary…

Algebraic Geometry · Mathematics 2024-11-19 Nikita Karpenko , Guangzhao Zhu

An optical imaging system forms an object image by recollecting light scattered by the object. However, intact optical information of the object delivered through the imaging system is deteriorated by imperfect optical elements and unwanted…

Optics · Physics 2017-03-28 SangYun Lee , Kyeoreh Lee , Seungwoo Shin , YongKeun Park

Given samples (x_1,...,x_m) and (z_1,...,z_n) which we believe are independent realizations of random variables X and Z respectively, where we further believe that Z=X+Y with Y independent of X, the problem is to estimate the distribution…

Computation · Statistics 2007-08-22 Colin Mallows

The mathematical analysis was conceived in XVII century in Newton and Leibniz works. The problem of logical rigor in definitions was considered by Arnauld and Nicole in "Logique ou l'art de penser". They were the first, who distinguished…

History and Overview · Mathematics 2015-02-25 G. Sinkevich

Deconvolution serves as a computational means of removing the effect of optical aberrations from recorded images and is employed in many technical and scientific fields of study. In most imaging scenarios the nature of the blurring kernel…

Image and Video Processing · Electrical Eng. & Systems 2018-10-18 Dean Wilding , Oleg Soloviev , Paolo Pozzi , Carlas Smith , Gleb Vdovin , Michel Verhaegen

In a given problem, the Bayesian statistical paradigm requires the specification of a prior distribution that quantifies relevant information about the unknowns of main interest external to the data. In cases where little such information…

Statistics Theory · Mathematics 2017-10-11 Alexander Terenin , David Draper

The paper gives a review of very recent results related to the Poncelet Theorem, on the occasion of its bicentennial. We are telling the story of one of the most beautiful theorems of Geometry, recalling for the general mathematical…

Exactly Solvable and Integrable Systems · Physics 2013-03-26 Vladimir Dragovic , Milena Radnovic

The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas,…

Neural and Evolutionary Computing · Computer Science 2015-12-08 Tim Taylor , Alan Dorin , Kevin Korb

Computational techniques which establish the stability of an evolution-boundary algorithm for a model wave equation with shift are incorporated into a well-posed version of the initial-boundary value problem for gravitational theory in…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Maria C. Babiuc , Bela Szilagyi , Jeffrey Winicour

It has been proposed that, since the origin of life and the ensuing evolution of biological species, a second evolutionary process has appeared on our planet. It is the evolution of culture-e.g., ideas, beliefs, and artifacts. Does culture…

Populations and Evolution · Quantitative Biology 2019-07-09 Liane Gabora , Diederik Aerts

Many fundamental questions concerning the emergence and subsequent evolution of eukaryotic exon-intron organization are still unsettled. Genome-scale comparative studies, which can shed light on crucial aspects of eukaryotic evolution,…

Populations and Evolution · Quantitative Biology 2007-05-23 Miklós Csűrös , J. Andrew Holey , Igor B. Rogozin

This work contains an exposition of foundations of the variational calculus in fibered manifolds. The emphasis is laid on the geometric aspects of the theory. Especially functionals defined by real functions (Lagrange functions) or…

Mathematical Physics · Physics 2007-05-23 Demeter Krupka

The Mullineux involution is an important map on $p$-regular partitions that originates from the modular representation theory of $\mathcal{S}_n$. In this paper we study the Mullineux transpose map and the generalized column regularization…

Combinatorics · Mathematics 2020-07-30 Allen Wang , Guangyi Yue

Deep learning models lack shift invariance, making them sensitive to input shifts that cause changes in output. While recent techniques seek to address this for images, our findings show that these approaches fail to provide…

Machine Learning · Computer Science 2025-02-28 Berken Utku Demirel , Christian Holz

We propose an image deconvolution algorithm when the data is contaminated by Poisson noise. The image to restore is assumed to be sparsely represented in a dictionary of waveforms such as the wavelet or curvelet transform. Our key…

Optimization and Control · Mathematics 2008-03-25 François-Xavier Dupé , Jalal Fadili , Jean Luc Starck

Although the theory of density evolution in maps and ordinary differential equations is well developed, the situation is far from satisfactory in continuous time systems with delay. This paper reviews some of the work that has been done…

Dynamical Systems · Mathematics 2022-11-07 Michael C. Mackey , Marta Tyran-Kamińska

This thesis is divided into two parts. The first one is composed of recollections on operad theory, model categories, simplicial homotopy theory, rational homotopy theory, Maurer-Cartan spaces, and deformation theory. The second part deals…

Algebraic Topology · Mathematics 2018-07-09 Daniel Robert-Nicoud

Denoising diffusion models have emerged as one of the most powerful generative models in recent years. They have achieved remarkable success in many fields, such as computer vision, natural language processing (NLP), and bioinformatics.…

Machine Learning · Computer Science 2023-02-23 Zhiye Guo , Jian Liu , Yanli Wang , Mengrui Chen , Duolin Wang , Dong Xu , Jianlin Cheng
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