Complex Data

复杂数据

• 批准号: CRC-2017-00189
• 负责人: Livi, Lorenzo
• 金额: $ 8.74万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=693128
• 关键词: Complex; Data

Many natural and man-made systems are now observable with a high level of detail, allowing us to investigate and understand phenomena with an unprecedented level of sophistication.However, data describing such systems require complex representations encoding both temporal and spatial information.The objectives of Dr. Livi's research program are to:Design data-driven methods to process spatio-temporal information represented as evolving graphs;Unravel the inner mechanisms explaining the functioning of (artificial) recurrent neural networks;Apply data-driven methods in structural biology and computational neuroscience for solving basic scientific problems having impact on society and healthcare.

许多自然和人造系统现在都可以观察到很高的细节，使我们能够以前所未有的复杂程度调查和理解现象。然而，描述这类系统的数据需要对时间和空间信息进行复杂的表示。利维博士的研究计划的目标是：设计数据驱动的方法来处理表示为演化图的时空信息；揭示解释(人工)递归神经网络功能的内在机制；将数据驱动的方法应用于结构生物学和计算神经科学，以解决对社会和医疗保健产生影响的基本科学问题。