| 
  • If you are citizen of an European Union member nation, you may not use this service unless you are at least 16 years old.

  • Finally, you can manage your Google Docs, uploads, and email attachments (plus Dropbox and Slack files) in one convenient place. Claim a free account, and in less than 2 minutes, Dokkio (from the makers of PBworks) can automatically organize your content for you.

View
 

ML_Meetings

Page history last edited by Kieran 6 days, 18 hours ago

Machine Learning in Astronomy Meetings

 

Regular fortnightly (i.e. every 2 weeks) informal zoom research meetings take place on https://uws.zoom.us/j/6448448129 and on the WSU Kingswood campus in room Y2.32 (the "Thinktorium"). Times were chosen by a Doodle poll, and will be revisited every 6 months.

 

Schedule of Meetings in 2021: 

  • 09/02/2021 1005 (AEDT) - Yuan-Sen Ting (ANU): "The Emergence of Deep Learning from A Physics Point of View". Slides Link. Download Link. Youtube Link.
  • 25/02/2021 1005 (AEDT) - Ashley Villar (Columbia University): "Anomaly Detection in Supernova-like Time Series"
  • 11/03/2021 1005 (AEDT) - John Wu (STSCI): "Insights on galaxy evolution and morpholoy using deep learning".
  • 25/03/2021 1005 (AEDT) - Kartheik Iyer (Dunlap): "Using Gaussian Processes to Decode the Star Formation History of Galaxies". 

 

Meetings are fortnightly at the time (time may not be accurate close to the daylight changeover period -  please check your local time against UTC)

 

 

UTC  Sydney (AEDT) Perth (AWST) Paris (CET)  Denver (MST) 
Wednesday 11:05PM
Thursday 10:05AM
Tuesday 7:05AM
Tuesday 12:05AM
Wednesday 4:05PM

 

 

How to join the meeting remotely (Note Zoom address has changed):

 

 

Format of Talks (suggestions for speakers)

The length is anything from 30 to 45mins - you choose. In any remaining time (the meeting is scheduled to last for up to 50 minutes) we will have an informal discussion about the topics you raise. I suggest you use a powerpoint/keynote/pdf, and expect people to chip in with questions, or even trigger a discussion, as you go along. I.e. the tone is relaxed and informal. Nobody is going to give you a hard time. Think of it as chatting with your peers about your work. Bear in mind that the audience ranges from data scientists who know little about astronomy to astronomers who know little about machine learning, so try to keep the jargon to a minimum, or explain It if you need to use it.

 

Recordings of Meetings in 2020

See this page

 

Recordings of Meetings in 2019

See this page

 

Recordings of Meetings in 2018 and earlier

See this page

 
Version:1.0 StartHTML:0000000105 EndHTML:0000038686 StartFragment:0000038405 EndFragment:0000038646 Stellenbosch University Stell

Comments (0)

You don't have permission to comment on this page.