The anomalous diffusion challenge: single trajectory characterisation as a competition
The anomalous diffusion challenge: single trajectory characterisation as a competition
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异常扩散挑战：单轨迹表征作为竞赛
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
C. Manzo
中科院分区：
文献类型：
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作者：
Gorka Muñoz;G. Volpe;M. Garcia;R. Metzler;M. Lewenstein;C. Manzo
偏离纯布朗运动，通常被称为反常扩散，在科学文献中得到了广泛的关注，以描述许多物理场景。已经开发了几种基于经典统计和机器学习方法的方法来表征实验数据中的异常扩散，这些数据通常作为粒子轨迹获取。为了评估和比较表征异常扩散的可用方法，我们组织了异常扩散（Andi）挑战赛（http：//www.andi-challenge.org/）。具体而言，Andi挑战将解决异常扩散表征的三个不同方面，即：（i）异常扩散指数的推断。(ii)基础扩散模型的识别。(iii)分割轨迹。每个问题包括不同数量的维度（1D，2D和3D）的子任务。为了比较各种方法，我们开发了一个专用的开源框架，用于模拟用于训练和测试数据集的异常扩散轨迹。该挑战赛于2020年3月1日启动，分为三个阶段。目前，第一阶段的参与是开放的。提交的作品将被自动评估，最高评分方法的性能将在即将发表的文章中进行彻底的分析和比较。
The deviation from pure Brownian motion, generally referred to as anomalous diffusion, has received large attention in the scientific literature to describe many physical scenarios. Several methods, based on classical statistics and machine learning approaches, have been developed to characterize anomalous diffusion from experimental data, which are usually acquired as particle trajectories. With the aim to assess and compare the available methods to characterize anomalous diffusion, we have organized the Anomalous Diffusion (AnDi) Challenge (http://www.andi-challenge.org/). Specifically, the AnDi Challenge will address three different aspects of anomalous diffusion characterization, namely: (i) Inference of the anomalous diffusion exponent. (ii) Identification of the underlying diffusion model. (iii) Segmentation of trajectories. Each problem includes sub-tasks for different number of dimensions (1D, 2D and 3D). In order to compare the various methods, we have developed a dedicated open-source framework for the simulation of the anomalous diffusion trajectories that are used for the training and test datasets. The challenge was launched on March 1, 2020, and consists of three phases. Currently, the participation to the first phase is open. Submissions will be automatically evaluated and the performance of the top-scoring methods will be thoroughly analyzed and compared in an upcoming article.