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ML for Earth System Modelling and Analytics workshop 2021

DKRZ/HZG/GERICS co-organize a workshop, supported by Helmholtz AI, to facilitate knowledge exchange and discussion about the state of the art and future directions of applying ML methods in Earth System modelling, analytics, and impact research.
When
May 03, 2021 02:30 PM to May 04, 2021 06:00 PM (Europe/Berlin / UTC200)
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To overcome limitations in computing and data analytics related to Earth System science, the uptake of artificial intelligence (AI) and machine learning (ML) methodologies is currently being explored. Multiple initiatives are now emerging to tackle open challenges such as subscale parametrization, detection of patterns and in-situ analysis, adoption of ML for alternative process models, or dedicated fast prediction systems to address specific end-user needs.

Following the first workshop held in February 2020, this second workshop will provide an update on the state of the art in applying and extending AI/ML techniques in topics relevant to Earth System science, from integrating ML with models to deriving new insights from observational data, to extending AI/ML to impact models and approaches. We call for contributions to the sessions, offering presentation and lightning talk slots for those interested in submitting an abstract (deadline for submission: March 19, 2021). Contributions are welcome from all participants, from updates on ongoing research activities and future plans to technical insights worthwhile to share.

The workshop will take place on the afternoons of May 03/04, 2021, from about 14:30-18:00 CEST. The workshop will be an exclusively online event. The workshop is co-organized by DKRZ, HZG and GERICS with support from Helmholtz AI.

Workshop co-organizers:
Laurens Bouwer (GERICS), Christopher Kadow (DKRZ), Tobias Weigel (DKRZ/Helmholtz AI), Eduardo Zorita (HZG)

 

Click here for registration and abstract submission

 

Workshop schedule: (in preparation)

The workshop will take place in the afternoon to allow participants from other timezones to join more easily.

 

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