Machine Learning in Climate Science

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Machine Learning in Climate Science

Machine Learning in Climate Science

@MachineClimate

Independent research group led by @bedartha at @uni_tue, within Cluster of Excellence @ml4science

Se unió Mart 2020
277 Siguiendo692 Seguidores
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Machine Learning in Climate Science
In this latest paper from our group, we shows how background SST's over the Pacific modulate propagation pathways of extreme rainfall in the Asian Mosoon domain. Excellent work led by @strnad_f involving also @schloer_jakob, @ruth_geen, Niklas Boers and @bedartha
Nature Communications@NatureComms

New study by @strnad_f et al. reveals distinct extreme #rainfall propagation modes driven by the Boreal Summer Intraseasonal Oscillation in the Indo-Pacific region that could offer potential for #earlywarnings. @machineclimate nature.com/articles/s4146…

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Machine Learning in Climate Science
News update: @schloer_jakob from our group defended his thesis on "A Data-Driven Perspective on ENSO Diversity" yesterday and has been awarded a Magna cum Laude! He has now moved on to his new job with the ECMWF in Bonn where he works on DL based S2S weather forecasts. Kudos!
Bedartha Goswami@bedartha

I feel extremely proud to announce that @schloer_jakob successfully defended his PhD thesis yesterday and graduated with a Magna cum Laude 😀 What's more, Jakob is _the_ first student I have ever graduated! Congratulations to Jakob and cheers!

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Climate Change AI
Climate Change AI@ClimateChangeAI·
Can't make it to #ICLR2024? We've got you covered! We are excited to announce that our full workshop on May 11 will be livestreamed - for free! 🎉🤓 For more info on the program & the link to the livestream, check our website: climatechange.ai/events/iclr2024
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Ulrike Luxburg
Ulrike Luxburg@UlrikeLuxburg·
Our exhibition about AI in Tübingen receives the Communicator Award! Thanks to Wiebke Ratzeburg and Guido Szymanska @StadtmuseumTue and to all the students who put so much effort in conceptualizing and creating the exhibition!
DFG public | @[email protected]@dfg_public

Der #Communicatorpreis 2024 geht an: Team "Cyber and the City"🎉@ulrikeluxburg, Tim Schaffarczik & Thomas Thiemeyer @uni_tue bringen m. einer Ausstellung das Thema #KI Menschen näher. Das Konzept kann modellhaft für kontrovers diskutierte Wissenschaftsthemen sein. Glückwunsch!

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Priya L. Donti
Priya L. Donti@priyald17·
The @ClimateChangeAI Summer School is back, featuring tons of awesome content and community-building on #AI for #climate action!💃 Registration for the virtual program (Jun-Jul) is now open 📚 Applications for the in-person program (Aug in Montreal) are open until April 14 😎
Climate Change AI@ClimateChangeAI

We're excited to announce the @ClimateChangeAI Summer School 2024!☀️ Are you an #AI expert who wants to tackle #ClimateChange? Are you a #climate expert trying to use #ML in your work? Are you curious about the topic? Apply & register now! Learn more👉climatechange.ai/events/summer_…

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Zeynep Akata
Zeynep Akata@zeynepakata·
🚀 Exciting Opportunity Alert! 🚀 🔍 Join us as a Postdoctoral Researcher (fully funded) at the Helmholtz Munich Institute for Explainable Machine Learning and TUM Chair of Interpretable and Reliable Machine Learning! @TU_Muenchen @Helmholtz_Munich @ELLISforEurope
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Science Magazine
Science Magazine@ScienceMagazine·
Deforestation of the Amazon may reach a critical point where abrupt declines in rainfall could cause widespread forest dieback, according to a new @ScienceAdvances Focus. scim.ag/4KX
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Bedartha Goswami
Bedartha Goswami@bedartha·
Excellent work from Jakobout as a preprint. ENSO events can essentially be well-explained with five fuzzy categories. The new-not-new one being the Extreme El Niño, which is an extreme EP event that's different in its dynamics
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Machine Learning in Climate Science
Preprint alert! @schloer_jakob uses dimensionality reduction methods (PCA, VAE) with Gaussian mixture models to classify ENSO events into 5 fuzzy groups based on multiple observational datasets & it turns out that extreme EP events form their own category with distinct dynamics!
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Florian Pappenberger
Florian Pappenberger@FPappenberger·
Be part of the team - ECMWF is building a world-leading, machine learning based probabilistic weather forecasting system jobs.ecmwf.int/Job/JobDetail?…
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Machine Learning in Climate Science
Excellent opportunity to be at the forefront of deep learning weather prediction and work with one of the best numerical weather prediction models
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Randy Chase
Randy Chase@DopplerChase·
Behold, the final copyedited version of the machine learning tutorial on neural networks is now available for you afternoon reading :) journals.ametsoc.org/view/journals/…
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