Discussion of "Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach"

被引：0
|
作者：
Datta, Abhirup [1 ]
机构：
[1] Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21218 USA
来源：
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS | 2023年 / 28卷 / 02期
关键词：
Machine learning; Deep neural network; Variational autoencoders; Climate data compression;
D O I：
10.1007/s13253-023-00539-0
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Huang et al (J Agric Biol Environ Stat, 2023, https://doi.org/10.1007/s13253-022-00 518-x) a suite of statistical models for storage-efficient climate model emulation. In this discussion, I review and explore possibility of using machine learning methods, in particular, deep neural network (DNN)-based variational autoencoders (VAE) for the same task of spatio-temporal climate data compression. I discuss the pros and cons of the statistical and the machine learning paradigms.
引用
收藏
页码：352 / 357
页数：6
相关论文
共 50 条
  • [41] Stochastic Approximation Trackers for Model-Based Search
    Joseph, Ajin George
    Bhatnagar, Shalabh
    2019 57TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON), 2019, : 741 - 748
  • [42] Model-Based Relative Entropy Stochastic Search
    Abdolmaleki, Abbas
    Lioutikov, Rudolf
    Lau, Nuno
    Reis, Luis Paulo
    Peters, Jan
    Neumann, Gerhard
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 28 (NIPS 2015), 2015, 28
  • [43] A Graphical Framework for Stochastic Model-Based Diagnosis
    Provan, Gregory
    2016 3RD CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), 2016, : 566 - 571
  • [44] Model-Based Relative Entropy Stochastic Search
    Abdolmaleki, Abbas
    Lioutikov, Rudolf
    Lau, Nuno
    Reis, Luis Paulo
    Peters, Jan
    Neumann, Gerhard
    PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'16 COMPANION), 2016, : 153 - 154
  • [45] Model-Based Testing for General Stochastic Time
    Gerhold, Marcus
    Hartmanns, Arnd
    Stoelinga, Marielle
    NASA FORMAL METHODS, NFM 2018, 2018, 10811 : 203 - 219
  • [46] Stochastic model-based optimization of irrigation scheduling
    Linker, Raphael
    AGRICULTURAL WATER MANAGEMENT, 2021, 243
  • [47] Embedding motion in model-based stochastic tracking
    Odobez, JM
    Gatica-Perez, D
    PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2, 2004, : 815 - 818
  • [48] Embedding motion in model-based stochastic tracking
    Odobez, Jean-Marc
    Gatica-Perez, Daniel
    Ba, Sileye O.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (11) : 3514 - 3530
  • [49] A Surrogate Model-Based Hybrid Approach for Stochastic Robust Double Row Layout Problem
    Wan, Xing
    Zuo, Xing-Quan
    Zhao, Xin-Chao
    MATHEMATICS, 2021, 9 (15)
  • [50] An Analytical Model-based Capacity Planning Approach for Building CSD-based Storage Systems
    Byun, Hongsu
    Jamil, Safdar
    Han, Jungwook
    Park, Sungyong
    Lee, Myungcheol
    Kim, Changsoo
    Choi, Beongjun
    Kim, Youngjae
    ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2024, 23 (06)
12345