Stream: ESDS

Topic: ICML 2021 Climate Change and Machine Learning

view this post on Zulip Katie Dagon (Apr 19 2021 at 18:41):

Please see the following announcement from Kasia Tokarska (ETH Zurich), apologies for cross posting:

Tackling Climate Change with Machine Learning
Workshop at International Conference on Machine Learning (ICML 2021)
Virtual: July 23rd or 24th, 2021

Workshop website: https://www.climatechange.ai/events/icml2021.html
Submission deadline: May 31st
Mentorship application deadline: April 28th
Contact: climatechangeai.icml2021@gmail.com
Informational webinars: April 23 (1:30 PM ET) and April 27 (9 AM ET)

We invite submissions of short papers using machine learning to address climate change. All machine learning techniques are welcome, from kernel methods to deep learning. Each submission should clearly illustrate why the application has (or could have) a pathway to impact regarding climate change. We highly encourage submissions that make their data publicly available.
Submissions are non-archival, and do not preclude future publication.

We strongly encourage authors to consider applying for our mentorship program (applications due April 28th), which will pair authors with mentors having complementary expertise. Applications to participate as a mentor are also open; we invite those from academia, industry, government, and beyond to apply. Please see the workshop website for application instructions and more details on the program.

Organizers:
Hari Prasanna Das (UC Berkeley)
Kasia Tokarska (ETH Zurich)
Maria João Sousa (IST, ULisboa)
Meareg Hailemariam (DAUST)
David Rolnick (Mila, McGill)
Xiaoxiang Zhu (TU Munich)
Yoshua Bengio (Mila, UdeM)

Last updated: Jan 30 2022 at 12:01 UTC