Network on multiScale Information, RePresentatIon and Estimation -- (INSPIRE)

当今社会正在经历一场数据采集和存储的革命。在医学成像、生物化学和生物信息学等领域，人们经常收集具有前所未有的异质性和复杂性的新形式的数据。随着数据采集继续取得成功，数据收集变得更容易执行，数据格式变得更加多样化，开发新工具以了解我们生活的世界的未决问题的数量正在增加，而不是减少。为了能够从数据中做出合理的推断，我们必须对其机制进行定量和准确的理解。由于这项任务在确定更复杂现象的产生方面固有的难度越来越大，必须汇集不同科学领域的专门知识，特别是信号处理、统计学和数学，以解决建模、表示和分析问题。尽管这是举世公认的事实，但上述领域的发展往往是不同的和不同步的。因此，这项申请建议建立一个研究人员网络，使用多尺度和相关方法研究结构化数据表示和推理问题。该网络寻求建立在现有的强大的英国集团的基础上，这些集团一直主要独立工作，将它们的专业知识和发展联系起来。通过建立一个共享信息和协作的虚拟卓越中心，并通过定期举行会议，我们力求确保拟议的网络节点之间有稳定和强有力的信息流动。这将对最初提议的成员产生更大的影响：在该网络的整个生命周期内，我们打算努力扩大其规模，并寻求形成一个包容性的虚拟英才中心，弥合各学科之间的差距。此外，在这一领域建立一个具有强大的多学科组成部分的网络，将有助于使用分析结构化数据形式的方法的领域，其中包括医学成像和金融等不同领域。通过为所有相关领域的研究生提供多学科互动和培训的自然论坛，我们寻求在下一代研究人员中培养多学科互动的精神，并确保网络对科学界的持久影响。我们是一个信息时代，只有通过投资开发收集和分析信息的工具，我们才有希望在明天的科学问题上取得进展。只有利用所有相关学科的专门知识，才能有效地完成这一发展，因此有必要按照该网络的建议，将所概述的研究领域联系起来。

Today's society is experiencing a revolution in data acquisition and storage. New forms of data with unprecedented levels of heterogeneity and complexity are collected routinely in areas such as medical imaging, biochemistry, and bioinformatics. As the success of data acquisition continues, and the collection of data become easier to implement, data formats become ever more diverse and the number of outstanding problems in developing new tools for understanding the world we live in, is increasing rather than diminishing. To be able to rationally make inferences from data, our understanding of its mechanism must be made quantitative and precise. With the increasing level of difficulty in this task inherent in qualifying the generation of more complex phenomena, expertise must be brought together from different areas of science, notably signal processing, statistics and mathematics, to tackle the problems of modelling, representation and analysis. Despite this universally acknowledged fact, developments in the aforementioned areas, are often divergent and unsynchronized. This application therefore proposes to establish a network of researchers, working on problems of structured data representation and inference using multiscale and related methods. The network seeks to build on existing strong UK groups that have been working mainly independently, by connecting their expertise and developments. By creating a virtual centre of excellence to share information and collaborate, and by holding regular meetings, we seek to ensure a steady and strong flow of information between the proposed network nodes. This will have an impact beyond the initially proposed membership: throughout the lifespan of the network we intend to work towards its expansion, and seek to form an inclusive virtual centre of excellence, bridging the gap between disciplines. Furthermore, the establishment of a network in this area with a strong multidisciplinary component, will feed into areas that use methods for analysis of structured forms of data, where examples include such disparate fields such as medical imaging and finance. By including a natural forum for multidisciplinary interaction and training of graduate students from all the related areas, we seek to foster a spirit of multidisciplinary interaction in the next generation of researchers, and secure a lasting impact of the network on the scientific community. Ours is an information age, and only by investing in the development of tools to collect and analyse information, can we hope to make headway into the scientific problems of tomorrow. This development can only be done effectively by using the expertise from all the relevant disciplines, and so it is necessary to connect the outlined areas of research, as proposed by this network.