社区所有版块导航
Python
python开源   Django   Python   DjangoApp   pycharm  
DATA
docker   Elasticsearch  
aigc
aigc   chatgpt  
WEB开发
linux   MongoDB   Redis   DATABASE   NGINX   其他Web框架   web工具   zookeeper   tornado   NoSql   Bootstrap   js   peewee   Git   bottle   IE   MQ   Jquery  
机器学习
机器学习算法  
Python88.com
反馈   公告   社区推广  
产品
短视频  
印度
印度  
Py学习  »  机器学习算法

‎ECMWF-欧空局关于地球观测和预测的机器学习研讨会‎(2022年11月14-17 日)

气象学家 • 4 年前 • 464 次点击  

Workshop motivation and description

The use of Machine Learning/Deep Learning (ML/DL) techniques is becoming widespread in a large and ever-growing number of application areas in Earth System Observation and Prediction (ESOP). Additionally, the scale, complexity and sophistication of the ML/DL technologies applied in ESOP has also increased considerably over the last few years, reflecting the growing uptake of ML/DL ideas in the ESOP communities and benefiting from increased interest of ML/DL domain scientists and of large commercial players. As a result, ML/DL tools are increasingly integrated in ESOP applications and in some areas they show promise of substituting traditional methodologies.

The third edition of the ECMWF–ESA Workshop on Machine Learning for Earth Observation and Prediction aims to provide an up-to-date snapshot of the state of the art in this rapidly evolving field and to facilitate discussion among scientists and practitioners about the current opportunities and challenges in the use of ML/DL technologies for ESOP.        

Thematic areas

Thematic areas that we expect to be covered in this workshop include:
1. Machine Learning for Earth Observations
2. Hybrid Machine Learning - Data Assimilation
3. Machine Learning for Model emulation and Model discovery
4. Machine Learning for user-oriented Earth Science applications
5. Machine learning at the edge and high-performance computing

Attendance

The workshop will be held at ECMWF Shinfield Park (Reading, UK) from 14 to 17 November 2022. While the main focus of the workshop is towards an in-person event, remote attendance will be possible.

Registration and abstract submission is now open. Follow the links in the menu on the left. 

声明:欢迎转载、转发本号原创内容,可留言区留言或者后台联系小编(微信:gavin7675)进行授权。气象学家公众号转载信息旨在传播交流,其内容由作者负责,不代表本号观点。文中部分图片来源于网络,如涉及作品内容、版权和其他问题,请后台联系小编处理。





往期推荐

★ ERA5-Land陆面高分辨率再分析数据(~16TB)

★ ERA5常用变量再分析数据(~11TB)

★ TRMM 3B42降水数据(Daily/3h)

★ 科研数据免费共享: GPM卫星降水数据

★ 气象圈子有人就有江湖,不要德不配位!

★ 请某气象公众号不要 “以小人之心,度君子之腹”!

★ EC数据商店推出Python在线处理工具箱

★ EC打造实用气象Python工具Metview

★ 机器学习简介及在短临天气预警中的应用

★ AMS推荐|气象学家-海洋学家的Python教程

★ Nature-地球系统科学领域的深度学习及理解

★ 采用神经网络与深度学习来预报降水、温度等


   欢迎加入气象学家交流群   

请备注:姓名/昵称-单位/学校-研究方向

(未备注的不通过申请)



❤️ 「气象学家」 点赞

Python社区是高质量的Python/Django开发社区
本文地址:http://www.python88.com/topic/138889