World Meeting of the International Society for Bayesian Analysis 2022

2022 年国际贝叶斯分析学会世界会议

基本信息

  • 批准号:
    2206934
  • 负责人:
  • 金额:
    $ 1.2万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-05-01 至 2023-04-30
  • 项目状态:
    已结题

项目摘要

This award provides travel support for US-based participants in the 2022 World Meeting of the International Society for Bayesian Analysis (ISBA), to be held from June 25 to July 1, 2022, in Montreal, Canada. The conference themes are theory, modeling, and applications of Bayesian statistics. The focus of this award is on funding for junior researchers (graduate students and postdoctoral researchers) from U.S.-based institutions to travel to the conference. Emphasis will be placed on supporting women and members of underrepresented groups. Participating in the conference will inform junior statisticians about key problems and methods that shape research in modern Bayesian statistics and provide them with opportunities to learn from more established researchers and to build mentoring and collaborative relationships. More information on the conference is available on the meeting web page: https://isbawebmaster.github.io/ISBA2022/Statisticians play an indispensable role in making decisions based on noisy, complex data structures. Statistical methods find application in myriad areas, including biomedical research, environmental science, finance, marketing, psychology, public health, and genomics. Within statistics, the Bayesian approach offers many appealing features: Bayesian methods provide a coherent framework for integrating information from different sources and communicating findings and conclusions using probabilities; Bayesian hierarchical models can capture different sources of variability in data and processes; relevant knowledge can be incorporated easily; and all relevant uncertainties are coherently propagated and incorporated into the final inference. Consequently, Bayesian analyses are commonplace across a wide variety of application areas. ISBA 2022 will bring together a diverse international community of researchers and practitioners who develop and use Bayesian statistical methods to share recent findings, exchange ideas, and discuss new, challenging questions. As a truly international meeting, it will provide participants with access to ideas and colleagues from other countries with whom they may not ordinarily interact. Meeting organizers hope to provide a venue that facilitates the exchange of ideas and cross-fertilization, is welcoming to young researchers, and promotes collaborations and interactions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该奖项为2022年6月25日至7月1日在加拿大蒙特利尔举行的国际贝叶斯分析学会(ISBA)2022年世界会议的美国与会者提供差旅支持。会议的主题是贝叶斯统计的理论、建模和应用。该奖项的重点是资助来自美国机构的初级研究人员(研究生和博士后研究人员)前往参加会议。重点将放在支持妇女和任职人数不足群体的成员上。参加会议将使初级统计学家了解影响现代贝叶斯统计学研究的关键问题和方法,并为他们提供向更成熟的研究人员学习并建立指导和合作关系的机会。有关会议的更多信息可在会议网页上获得:https://isbawebmaster.github.io/ISBA2022/Statisticians在基于嘈杂、复杂的数据结构做出决策方面发挥着不可或缺的作用。统计学方法在许多领域都有应用,包括生物医学研究、环境科学、金融、市场营销、心理学、公共卫生和基因组学。在统计学中,贝叶斯方法提供了许多吸引人的特征:贝叶斯方法提供了一个连贯的框架,用于整合来自不同来源的信息,并使用概率传达结果和结论;贝叶斯分层模型可以捕获数据和过程中不同的可变性来源;相关知识可以轻松纳入;所有相关的不确定性被连贯地传播并纳入最终推理。因此,贝叶斯分析在广泛的应用领域中很常见。ISBA 2022将汇集由研究人员和从业人员组成的多样化的国际社区,他们开发和使用贝叶斯统计方法来分享最新的发现,交流想法,并讨论新的、具有挑战性的问题。作为一次真正的国际会议,它将为与会者提供接触其他国家的想法和同事的机会,而他们通常不会与这些国家进行互动。会议组织者希望提供一个促进思想交流和交叉滋养的场所,欢迎年轻的研究人员,并促进合作和互动。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(0)
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会议论文数量(0)
专利数量(0)

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Matthias Katzfuss其他文献

Climate Change Detection and Attribution
气候变化检测和归因
Learning Non-Gaussian Spatial Distributions Via Bayesian Transport Maps with Parametric Shrinkage
Locally Anisotropic Nonstationary Covariance Functions on the Sphere
球面上的局部各向异性非平稳协方差函数
Linear-Cost Vecchia Approximation of Multivariate Normal Probabilities
多元正态概率的线性成本 Vecchia 近似
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jian Cao;Matthias Katzfuss
  • 通讯作者:
    Matthias Katzfuss

Matthias Katzfuss的其他文献

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{{ truncateString('Matthias Katzfuss', 18)}}的其他基金

Collaborative Research: Scalable Gaussian-Process Methods for Spatial Statistics and Machine Learning
合作研究:空间统计和机器学习的可扩展高斯过程方法
  • 批准号:
    1953005
  • 财政年份:
    2020
  • 资助金额:
    $ 1.2万
  • 项目类别:
    Standard Grant
CAREER: Data Assimilation for Massive Spatio-Temporal Systems Using Multi-Resolution Filters
职业:使用多分辨率滤波器对大规模时空系统进行数据同化
  • 批准号:
    1654083
  • 财政年份:
    2017
  • 资助金额:
    $ 1.2万
  • 项目类别:
    Continuing Grant
Statistical Analysis of Massive Spatio-Temporal Datasets Using Distributed Computing
利用分布式计算对海量时空数据集进行统计分析
  • 批准号:
    1521676
  • 财政年份:
    2015
  • 资助金额:
    $ 1.2万
  • 项目类别:
    Standard Grant

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