Michael Bertolacci
@mikebertolacci
Senior Lecturer in statistics at UWA (@uwanews). Everything is latently Gaussian: change my mind.
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I'm very excited to continue our work analysing the data from NASA's OCO satellites, co-lead by @NoelCressie, @andrewzm, and @bea_buks, along with students @joshhjacobson, Alan Pearse, and Daemon Kennett. A dream team!
Dr @mikebertolacci and his team have received three years' funding from @NASA as members of the #NASA Orbiting Carbon Observatory Science Team. 👏🪐 #UOWResearch
Out today: short paper from me + colleagues on policy challenges at the AI research frontier. The paper (based on an event we co-ran with @GoogleDeepMind) explores foreseeable extensions of existing AI technologies, the risks they might pose, and what policymakers can do. 🧵:
📝 New workshop report! 📝 If you’ve heard the term “frontier AI” over the last few months, this one’s for you. The paper shares key themes and recommendations from a roundtable that CSET cohosted with @GoogleDeepMind. cset.georgetown.edu/publication/sk…
We invite you to meet the keynote speakers @ASC2023 and OZCOTS 2023, 10-15 December 2023 @! Learn more here: bit.ly/42yvLo9 @_MargaritaMB @andrewzm #University #Stats #statistics #DataScience @ABSStats @DiscoverAMSI @AMSIschools @acspri @ssa_ecssn
Nice to see this come out—it was wonderful to play a small part in this work. Well done @BKAByrne for leading this!
Assessing a country's carbon stock from atmospheric measurements is challenging. So proud of our team contributing to this international study done in support of the UNFCCC global stocktake nasa.gov/feature/jpl/na… @uowcei @uowresearch @uowniasra @mikebertolacci @NoelCressie
Stoked to see this come out - a little piece about our work on the carbon cycle in the latest issue of @signmagazine.
Congratulations to @uowcei members @NoelCressie @andrewzm @joshhjacobson and @mikebertolacci on their feature article in the newest issue of @signmagazine 🌎CO2 data from @NASAEartht's #OCO2 satellite is seen through the eyes of #WOMBAT
@SMAS presents the Annual Statistical Science Lecture on Thurs17Nov22 @UOW given by Professor Michael I. Jordan. #DataScience #RStats #StatsTwitter #machinelearning. More details in the registration link eventbrite.com.au/e/2022-statist…
Join Dr @mikebertolacci from the #UOW Centre for Environmental Informatics @uowniasra for an online discussion about the increase in greenhouse gases on Earth. 👉 uow.to/3yoibXp #GCCW #UOWGCCW
If you're into statistical deep learning, this (FREE!) workshop in Sydney might interest you—I'll be there.
There are still a few spots left at the "Workshop on Statistical Deep Learning", which is full of exciting talks and networking opportunities! Sydney CBD 24-25 October 2022. Registration closes 30 Sep 2022. andrewzm.github.io/deepspat-websi…
🚨🌍check out our new preprint estimating global N2O emissions using a hierarchical Bayesian inversion: egusphere.copernicus.org/preprints/2022… @angharadstell @mikebertolacci @andrewzm @TheOtherMRigby @AnitaGanesan and many others!
Ever wonder how climate scientists monitor when and where #CO2 enters and exits the atmosphere? Our new post for @uowcei provides an overview of the process and the fancy Bayesian framework #WOMBAT for CO2 flux estimation 👇 @NoelCressie @mikebertolacci uow.edu.au/niasra/our-res…
Go @AtmosJennyF!!! Oh, well done!
Associate Professor Jenny Fisher (@AtmosJennyF) has been awarded the 2022 Anton Hales Medal, which recognises research in the Earth sciences. She is exploring air pollution by researching the atmospheric chemistry of trace gases. @UOW #Honorifics22 science.org.au/supporting-sci…
"Everyone who confuses correlation with causation eventually ends up dead." Favorite new way to teach this, hands down.
This, but statisticians.
Blog post describing the key ideas behind our now published #CO2 flux inversion framework, WOMBAT. @uowcei @mikebertolacci @NoelCressie @AtmosJennyF @TheOtherMRigby andrewzm.wordpress.com/?p=1098&previe…
andrewzm.wordpress.com
WOMBAT! (for estimating CO₂ sources and sinks)
In 2015, together with Noel Cressie, I started looking at the problem of estimating sources and sinks of greenhouse gases such as methane and carbon dioxide using ideas from spatial and spatio-temp…
Maybe instead of just epistemic and aleatoric uncertainty, we need a third option which is how certain you are that there aren't bugs in your analysis code.
Maybe instead of just epistemic and aleatoric uncertainty, we need a third option which measures how uncertain you are about which of these words to use
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