检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Eberle-Blick, Sarah Pohjola, Valter Institute of Mathematics Goethe University Frankfurt Germany Unit of Applied and Computational Mathematics University of Oulu Finland

We derive a linearized version of the monotonicity method for shape reconstruction using time harmonic elastic waves. The linearized method provides an efficient version of the method, drastically reducing computation time. Here we show that the linearized method has some additional advantages. The linearized method can in particular be used to obtain additional information on the material parameters, and is able to partially separate and identify the supports of the Lamé *** Codes 35R30, 35J05 Copyright © 2024, The Authors. All rights reserved.

关键词： Elastic waves

来源：评论

学校读者我要写书评

暂无评论

Overcoming Saturation in Density Ratio Estimation by Iterated Regularization 41

Overcoming Saturation in Density Ratio Estimation by Iterate...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Gruber, Lukas Holzleitner, Markus Lehner, Johannes Hochreiter, Sepp Zellinger, Werner ELLIS Unit Linz LIT AI Lab Institute for Machine Learning Johannes Kepler University Linz Austria MaLGa Center Department of Mathematics University of Genoa Italy NXAI GmbH Linz Austria Johann Radon Institute for Computational and Applied Mathematics Austrian Academy of Sciences Austria

Estimating the ratio of two probability densities from finitely many samples, is a central task in machine learning and statistics. In this work, we show that a large class of kernel methods for density ratio estimation suffers from error saturation, which prevents algorithms from achieving fast error convergence rates on highly regular learning problems. To resolve saturation, we introduce iterated regularization in density ratio estimation to achieve fast error rates. Our methods outperform its non-iteratively regularized versions on benchmarks for density ratio estimation as well as on large-scale evaluations for importance-weighted ensembling of deep unsupervised domain adaptation models. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Gamma ray multiplicity of a^(240)Pu solid sphere simulated by JMCT

引用

Nuclear Science and Techniques 2022年第5期33卷 8-15页

作者： Huan-Huan Ding Fan Gao Chang-Bing Lu Rui Li Chen-Guang Li Zhao-Hong Mo Dun-Fu Shi Ming Su De-Shan Zhao Mao-Bing Shuai Zhong-Hua Xiong Bin-Yuan Xia Yun Bai Institute of Materials China Academy of Engineering PhysicsMianyang 621908China The 93147th Unit of PLA Mianyang 621000China CAEP Software Center for High Performance Numerical Simulation Beijing 100088China Institute of Applied Physics and Computational Mathematics Beijing 100088China

Determining the mass of plutonium metal is an important research objective in the field of nuclear material accounting and *** on the 3D neutron and photon transport code JMCT(Jointed Monte Carlo Transport),the gamma ray multiplicity of ^(240)Pu was simulated in this study,and the average number of gamma rays leaking from ^(240)Pu solid spheres with different masses was also *** simulation results show that there is a oneto-one correspondence between the average number of gamma rays and the mass of ^(240)Pu solid spheres in the range of 0.50–3.00 *** result provides a basis for using the average number of gamma rays to account for the mass of ^(240)Pu.

关键词： ^(240)Pu JMCT Gammaraymultiplicity Solid sphere mass Surface-to-volumeratio

来源：评论

学校读者我要写书评

暂无评论

ON THE SPECIALIZATION OF NEURAL MODULES 11

ON THE SPECIALIZATION OF NEURAL MODULES

引用

11th International Conference on Learning Representations, ICLR 2023

作者： Jarvis, Devon Klein, Richard Rosman, Benjamin Saxe, Andrew M. School of Computer Science and Applied Mathematics University of the Witwatersrand South Africa Gatsby Computational Neuroscience Unit Sainsbury Wellcome Centre UCL United Kingdom CIFAR Azrieli Global Scholar CIFAR United Kingdom

A number of machine learning models have been proposed with the goal of achieving systematic generalization: the ability to reason about new situations by combining aspects of previous experiences. These models leverage compositional architectures which aim to learn specialized modules dedicated to structures in a task that can be composed to solve novel problems with similar structures. While the compositionality of these architectures is guaranteed by design, the modules specializing is not. Here we theoretically study the ability of network modules to specialize to useful structures in a dataset and achieve systematic generalization. To this end we introduce a minimal space of datasets motivated by practical systematic generalization benchmarks. From this space of datasets we present a mathematical definition of systematicity and study the learning dynamics of linear neural modules when solving components of the task. Our results shed light on the difficulty of module specialization, what is required for modules to successfully specialize, and the necessity of modular architectures to achieve systematicity. Finally, we confirm that the theoretical results in our tractable setting generalize to more complex datasets and non-linear architectures. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

INVERSE SCATTERING PROBLEMS FOR NON-LINEAR WAVE EQUATIONS ON LORENTZIAN MANIFOLDS

arXiv

引用

arXiv 2024年

作者： Alexakis, Spyros Isozaki, Hiroshi Lassas, Matti Tyni, Teemu Department of Mathematics University of Toronto Canada College of Mathematics University of Tsukuba Japan Department of Mathematics and Statistics University of Helsinki Finland Research Unit of Applied and Computational Mathematics University of Oulu Finland

We show that an inverse scattering problem for a semilinear wave equation can be solved on a manifold having an asymptotically Minkowskian infinity, that is, scattering functionals determine the topology, differentiable structure, and the conformal type of the manifold. Moreover, the metric and the coefficient of the non-linearity are determined up to a multiplicative transformation. The manifold on which the inverse problem is considered is allowed to be an open, globally hyperbolic manifold which may have non-trivial topology or several infinities (i.e., ends) of which at least one has to be of the asymptotically Minkowskian type. To formulate the inverse problems we define a new type of data, non-linear scattering functionals, which are defined also in the cases where the classically defined scattering operators are not well-defined. This makes it possible to solve inverse problems also in cases where some of the incoming waves lead to a blow-up of the scattered solution. We use non-linear interaction of waves as a beneficial tool that helps to solve the inverse problem. The corresponding inverse problem for the linear wave equation still remains *** Codes 35R30, 35L05, 83C05 Copyright © 2024, The Authors. All rights reserved.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

引用

Frontiers of Structural and Civil Engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

来源：评论

学校读者我要写书评

暂无评论

Well-posedness and inverse problems for semilinear nonlocal wave equations

引用

Nonlinear Analysis, Theory, Methods and Applications 2024年 247卷

作者： Lin, Yi-Hsuan Tyni, Teemu Zimmermann, Philipp Department of Applied Mathematics National Yang Ming Chiao Tung University Hsinchu Taiwan Research Unit of Applied and Computational Mathematics University of Oulu Finland Department of Mathematics ETH Zurich Zürich Switzerland Departament de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain

This article is devoted to forward and inverse problems associated with time-independent semilinear nonlocal wave equations. We first establish comprehensive well-posedness results for some semilinear nonlocal wave equations. The main challenge is due to the low regularity of the solutions of linear nonlocal wave equations. We then turn to an inverse problem of recovering the nonlinearity of the equation. More precisely, we show that the exterior Dirichlet-to-Neumann map uniquely determines homogeneous nonlinearities of the form f(x,u) under certain growth conditions. On the other hand, we also prove that initial data can be determined by using passive measurements under certain nonlinearity conditions. The main tools used for the inverse problem are the unique continuation principle of the fractional Laplacian and a Runge approximation property. The results hold for any spatial dimension n∈N. © 2024 The Author(s)

关键词： Wave equations

来源：评论

学校读者我要写书评

暂无评论

Modelling the unexpected dynamics of COVID-19 in Manaus,Brazil

引用

Infectious Disease Modelling 2024年第2期9卷 557-568页

作者： Daihai He Yael Artzy-Randrup Salihu S.Musa Tiago Gräf Felipe Naveca Lewi Stone Department of Applied Mathematics Hong Kong Polytechnic UniversityHong Kong SARChina Department of Theoretical and Computational Ecology IBEDUniversity of AmsterdamAmsterdamNetherlands Department of Genomics and Computational Biology University of Massachusetts Chan Medical SchoolWorcesterMA01605USA Department of Mathematics Aliko Dangote University of Science and TechnologyKanoNigeria Instituto Gonçalo Moniz FiocruzSalvadorBahiaBrazil Instituto Leônidas e Maria Deane FiocruzManausBrazil Mathematical Sciences School of ScienceRMIT UniversityMelbourneAustralia Biomathematics Unit School of ZoologyFaculty of Life SciencesTel Aviv UniversityTel AvivIsrael

In late March 2020,SARS-CoV-2 arrived in Manaus,Brazil,and rapidly developed into a large-scale epidemic that collapsed the local health system and resulted in extreme death *** key studies reported that∼76%of residents of Manaus were infected(attack rate AR≃76%)by October 2020,suggesting protective herd immunity had been *** this,an unexpected second wave of COVID-19 struck again in November and proved to be larger than the first,creating a catastrophe for the unprepared *** has been suggested that this could be possible if the second wave was driven by ***,it is widely reported that reinfections were at a low rate(before the emergence of Omicron),and reinfections tend to be ***,we use novel methods to model the epidemic from mortality data without considering reinfection-caused deaths and evaluate the impact of interventions to explain why the second wave *** method fits a“flexible”reproductive numberR_(0)(t)that changes over the epidemic,and it is demonstrated that the method can successfully reconstruct R_(0)(t)from simulated *** Manaus,the method finds AR≃34%by October 2020 for the first wave,which is far less than required for herd immunity yet in-line with seroprevalence *** work is complemented by a two-strain *** genomic data,the model estimates transmissibility of the new P.1 virus lineage as 1.9 times higher than that of the ***,an age class model variant that considers the high mortality rates of older adults show very similar *** models thus provide a reasonable explanation for the two-wave dynamics in Manaus without the need to rely on large reinfection rates,which until now have only been found in negligible to moderate numbers in recent surveillance efforts.

关键词： Modelling COVID-19 Reproduction number Herd immunity Reinfection

来源：评论

学校读者我要写书评

暂无评论

WELL-POSEDNESS AND INVERSE PROBLEMS FOR SEMILINEAR NONLOCAL WAVE EQUATIONS

arXiv

引用

arXiv 2024年

作者： Lin, Yi-Hsuan Tyni, Teemu Zimmermann, Philipp Department of Applied Mathematics National Yang Ming Chiao Tung University Hsinchu Taiwan Unit of Applied and Computational Mathematics University of Oulu Finland Department of Mathematics ETH Zurich Zürich Switzerland Departament de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain

This article is devoted to forward and inverse problems associated with time-independent semilinear nonlocal wave equations. We first establish comprehensive well-posedness results for some semilinear nonlocal wave equations. The main challenge is due to the low regularity of the solutions of linear nonlocal wave equations. We then turn to an inverse problem of recovering the nonlinearity of the equation. More precisely, we show that the exterior Dirichlet-to-Neumann map uniquely determines homogeneous nonlinearities of the form f (x, u) under certain growth conditions. On the other hand, we also prove that initial data can be determined by using passive measurements under certain nonlinearity conditions. The main tools used for the inverse problem are the unique continuation principle of the fractional Laplacian and a Runge approximation property. The results hold for any spatial dimension n ∈ .MSC Codes Primary 35R30, secondary 26A33, 42B37 Copyright © 2024, The Authors. All rights reserved.

关键词： Wave equations

来源：评论

学校读者我要写书评

暂无评论

ADDRESSING PARAMETER CHOICE ISSUES IN UNSUPERVISED DOMAIN ADAPTATION BY AGGREGATION 11

ADDRESSING PARAMETER CHOICE ISSUES IN UNSUPERVISED DOMAIN AD...

引用

11th International Conference on Learning Representations, ICLR 2023

作者： Dinu, Marius-Constantin Holzleitner, Markus Beck, Maximilian Nguyen, Duc Hoan Huber, Andrea Eghbal-Zadeh, Hamid Moser, Bernhard A. Pereverzyev, Sergei V. Hochreiter, Sepp Zellinger, Werner ELLIS Unit Linz and LIT AI Lab Institute for Machine Learning Johannes Kepler University Linz Austria Dynatrace Research Austria Institute of Advanced Research in Artificial Intelligence Austria Software Competence Center Hagenberg Austria Johann Radon Institute for Computational and Applied Mathematics Austrian Academy of Sciences Austria

We study the problem of choosing algorithm hyper-parameters in unsupervised domain adaptation, i.e., with labeled data in a source domain and unlabeled data in a target domain, drawn from a different input distribution. We follow the strategy to compute several models using different hyper-parameters, and, to subsequently compute a linear aggregation of the models. While several heuristics exist that follow this strategy, methods are still missing that rely on thorough theories for bounding the target error. In this turn, we propose a method that extends weighted least squares to vector-valued functions, e.g., deep neural networks. We show that the target error of the proposed algorithm is asymptotically not worse than twice the error of the unknown optimal aggregation. We also perform a large scale empirical comparative study on several datasets, including text, images, electroencephalogram, body sensor signals and signals from mobile phones. Our method outperforms deep embedded validation (DEV) and importance weighted validation (IWV) on all datasets, setting a new state-of-the-art performance for solving parameter choice issues in unsupervised domain adaptation with theoretical error guarantees. We further study several competitive heuristics, all outperforming IWV and DEV on at least five datasets. However, our method outperforms each heuristic on at least five of seven datasets. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：