arXiv - STAT - Applications最新文献_第8页

Nested Fusion: A Method for Learning High Resolution Latent Structure of Multi-Scale Measurement Data on Mars 嵌套融合：学习火星多尺度测量数据高分辨率潜在结构的方法

arXiv - STAT - Applications Pub Date : 2024-08-24 DOI: arxiv-2409.05874

Austin P. Wright, Scott Davidoff, Duen Horng Chau

{"title":"Nested Fusion: A Method for Learning High Resolution Latent Structure of Multi-Scale Measurement Data on Mars","authors":"Austin P. Wright, Scott Davidoff, Duen Horng Chau","doi":"arxiv-2409.05874","DOIUrl":"https://doi.org/arxiv-2409.05874","url":null,"abstract":"The Mars Perseverance Rover represents a generational change in the scale of\u0000measurements that can be taken on Mars, however this increased resolution\u0000introduces new challenges for techniques in exploratory data analysis. The\u0000multiple different instruments on the rover each measures specific properties\u0000of interest to scientists, so analyzing how underlying phenomena affect\u0000multiple different instruments together is important to understand the full\u0000picture. However each instrument has a unique resolution, making the mapping\u0000between overlapping layers of data non-trivial. In this work, we introduce\u0000Nested Fusion, a method to combine arbitrarily layered datasets of different\u0000resolutions and produce a latent distribution at the highest possible\u0000resolution, encoding complex interrelationships between different measurements\u0000and scales. Our method is efficient for large datasets, can perform inference\u0000even on unseen data, and outperforms existing methods of dimensionality\u0000reduction and latent analysis on real-world Mars rover data. We have deployed\u0000our method Nested Fusion within a Mars science team at NASA Jet Propulsion\u0000Laboratory (JPL) and through multiple rounds of participatory design enabled\u0000greatly enhanced exploratory analysis workflows for real scientists. To ensure\u0000the reproducibility of our work we have open sourced our code on GitHub at\u0000https://github.com/pixlise/NestedFusion.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":"184 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Topological Gaussian Mixture Model for Bone Marrow Morphology in Leukaemia 白血病骨髓形态学拓扑高斯混杂模型

arXiv - STAT - Applications Pub Date : 2024-08-24 DOI: arxiv-2408.13685

Qiquan Wang, Anna Song, Antoniana Batsivari, Dominique Bonnet, Anthea Monod

引用次数: 0

When is truncated stop loss optimal? 什么情况下截断止损是最佳选择？

arXiv - STAT - Applications Pub Date : 2024-08-23 DOI: arxiv-2408.12933

Erik Bølviken, Yinzhi Wang

引用次数: 0

Broad versus narrow research questions in evidence synthesis: a parallel to (and plea for) estimands 证据综述中的宽泛研究问题与狭隘研究问题：与估算（和恳求）估算相似

arXiv - STAT - Applications Pub Date : 2024-08-23 DOI: arxiv-2408.12932

Antonio Remiro-Azócar, Anders Gorst-Rasmussen

引用次数: 0

Variational inference of effective range parameters for ${}^3$He-${}^4$He scattering {}^3$He-${}^4$He散射有效范围参数的变量推断

arXiv - STAT - Applications Pub Date : 2024-08-23 DOI: arxiv-2408.13250

Andrius Burnelis, Vojta Kejzlar, Daniel R. Phillips

引用次数: 0

Causal Hierarchy in the Financial Market Network -- Uncovered by the Helmholtz-Hodge-Kodaira Decomposition 亥姆霍兹-霍奇-柯达伊拉分解法揭示的金融市场网络中的因果层次结构

arXiv - STAT - Applications Pub Date : 2024-08-23 DOI: arxiv-2408.12839

Tobias Wand, Oliver Kamps, Hiroshi Iyetomi

引用次数: 0

A Multivariate Space-Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt Pinatubo Eruptio 表征皮纳图博火山爆发后大气影响的多变量时空动态模型

arXiv - STAT - Applications Pub Date : 2024-08-23 DOI: arxiv-2408.13392

Robert Garrett, Lyndsay Shand, J. Gabriel Huerta

{"title":"A Multivariate Space-Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt Pinatubo Eruptio","authors":"Robert Garrett, Lyndsay Shand, J. Gabriel Huerta","doi":"arxiv-2408.13392","DOIUrl":"https://doi.org/arxiv-2408.13392","url":null,"abstract":"The June 1991 Mt. Pinatubo eruption resulted in a massive increase of sulfate\u0000aerosols in the atmosphere, absorbing radiation and leading to global changes\u0000in surface and stratospheric temperatures. A volcanic eruption of this\u0000magnitude serves as a natural analog for stratospheric aerosol injection, a\u0000proposed solar radiation modification method to combat the warming climate. The\u0000impacts of such an event are multifaceted and region-specific. Our goal is to\u0000characterize the multivariate and dynamic nature of the climate impacts\u0000following the Mt. Pinatubo eruption. We developed a multivariate space-time\u0000dynamic linear model to understand the full extent of the spatially- and\u0000temporally-varying impacts. Specifically, spatial variation is modeled using a\u0000flexible set of basis functions for which the basis coefficients are allowed to\u0000vary in time through a vector autoregressive (VAR) structure. This novel model\u0000is caste in a Dynamic Linear Model (DLM) framework and estimated via a\u0000customized MCMC approach. We demonstrate how the model quantifies the\u0000relationships between key atmospheric parameters following the Mt. Pinatubo\u0000eruption with reanalysis data from MERRA-2 and highlight when such model is\u0000advantageous over univariate models.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Web-Based Solution for Federated Learning with LLM-Based Automation 基于 LLM 自动化的联合学习网络解决方案

arXiv - STAT - Applications Pub Date : 2024-08-23 DOI: arxiv-2408.13010

Chamith Mawela, Chaouki Ben Issaid, Mehdi Bennis

{"title":"A Web-Based Solution for Federated Learning with LLM-Based Automation","authors":"Chamith Mawela, Chaouki Ben Issaid, Mehdi Bennis","doi":"arxiv-2408.13010","DOIUrl":"https://doi.org/arxiv-2408.13010","url":null,"abstract":"Federated Learning (FL) offers a promising approach for collaborative machine\u0000learning across distributed devices. However, its adoption is hindered by the\u0000complexity of building reliable communication architectures and the need for\u0000expertise in both machine learning and network programming. This paper presents\u0000a comprehensive solution that simplifies the orchestration of FL tasks while\u0000integrating intent-based automation. We develop a user-friendly web application\u0000supporting the federated averaging (FedAvg) algorithm, enabling users to\u0000configure parameters through an intuitive interface. The backend solution\u0000efficiently manages communication between the parameter server and edge nodes.\u0000We also implement model compression and scheduling algorithms to optimize FL\u0000performance. Furthermore, we explore intent-based automation in FL using a\u0000fine-tuned Language Model (LLM) trained on a tailored dataset, allowing users\u0000to conduct FL tasks using high-level prompts. We observe that the LLM-based\u0000automated solution achieves comparable test accuracy to the standard web-based\u0000solution while reducing transferred bytes by up to 64% and CPU time by up to\u000046% for FL tasks. Also, we leverage the neural architecture search (NAS) and\u0000hyperparameter optimization (HPO) using LLM to improve the performance. We\u0000observe that by using this approach test accuracy can be improved by 10-20% for\u0000the carried out FL tasks.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Does Spatial Information Improve Influenza Forecasting? 空间信息能否改善流感预测？

arXiv - STAT - Applications Pub Date : 2024-08-22 DOI: arxiv-2408.12722

Gabrielle Thivierge, Aaron Rumack, F. William Townes

引用次数: 0

Evaluating Four Methods for Detecting Differential Item Functioning in Large-Scale Assessments with More Than Two Groups 评估在有两个以上组别的大规模评估中检测项目功能差异的四种方法

arXiv - STAT - Applications Pub Date : 2024-08-21 DOI: arxiv-2408.11922

Dandan Chen Kaptur, Jinming Zhang

引用次数: 0