@qed404

Applied math grad student @ Dartmouth College

jlindbloom.github.io/
Joined October 2020
  • Tweets110
  • Following561
  • Followers68
11Media
Jonathan Lindbloom retweeted
SIAM@TheSIAMNewsAug 27
On the SIAM News Blog, Apoorv Srivastava explores the value of #binary observations for #DataAssimilation using a parsimonious model of COVID-19 viral dynamics. He demonstrates that these observations can reduce #uncertainty. Check it out! #SIAMCT25 siam.org/publications/siam-n…
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Jonathan Lindbloom retweeted
GOLD-UE@GOLDartmouth10 May 2024
DARTMOUTH IS WITHHOLDING PAY - DONATE TO OUR STRIKE FUND: tinyurl.com/donate-gold
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"A Practical Introduction to Quantum Computing" (by Casey Dowdle and James Whitfield, in @TheSIAMNews): sinews.siam.org/Details-Page…

A Practical Introduction to Quantum Computing | SIAM

Viewing quantum mechanics as an extension of probability theory removes much of the surrounding mystery.

siam.org
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Jonathan Lindbloom retweeted
GOLD-UE@GOLDartmouth1 May 2024
Dartmouth has ordered the removal of our picket line playpen. This effectively removes the only form of childcare available to our members.
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Jonathan Lindbloom retweeted
Fondazione Cmcc@CmccClimate28 Feb 2024
#SaveTheDate | "Generalized Sparsity-Promoting Solvers and Uncertainty Quantification for Bayesian Inverse Problems" 🌐 CMCC Webinar 📅 05 March 2024 | 11:00 CET 🎙️Speaker: Jonathan Lindbloom, Darmouth College ➡️ Register here to attend: ow.ly/2maC50QI6U8
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Jonathan Lindbloom, Jan Glaubitz, Anne Gelb: Generalized sparsity-promoting solvers for Bayesian inverse problems: Versatile sparsifying transforms and unknown noise variances arxiv.org/abs/2402.16623 arxiv.org/pdf/2402.16623

Generalized sparsity-promoting solvers for Bayesian inverse...

Bayesian hierarchical models can provide efficient algorithms for finding sparse solutions to ill-posed inverse problems. The models typically comprise a conditionally Gaussian prior model for the...

arxiv.org
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Hmmm
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Wow
This Post is from an account that no longer exists. Learn more
Jonathan Lindbloom retweeted
Jaime Sevilla
@Jsevillamol3 Jun 2022
New issue of @NunoSempere's forecasting newsletter is out! Featuring work by @qed404 and yours truly forecasting.substack.com/p/f…
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Want to forecast expected minimum and maximum values (from extreme value theory)? fmax is a new (experimental) package based on PyMC for that purpose. Example: github.com/jlindbloom/fmax/b… By @Jsevillamol and jlindbloom.
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What's better than MCMC? MCMCMC? citeseerx.ist.psu.edu/viewdo…
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Looks pretty awesome! Bummed I’ll be busy…
Luigi Acerbi@AcerbiLuigi10 Mar 2022
Curious about probabilistic machine learning? Do you often wonder what would Bayes and Laplace do if they had access to modern computers? Join us in Helsinki 🇫🇮 on June 13-17 for the 3rd Nordic Probabilistic AI School (#ProbAI)! probabilistic.ai/ 1/
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Jonathan Lindbloom retweeted
Thomas Wiecki@twiecki5 Mar 2022
Any reason why economists love deriving custom Gibbs samplers for their models which they then hand-code in FORTRAN? Pretty sure most papers can be reduced to 10 lines of PyMC code.
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Jonathan Lindbloom retweeted
Kevin Kwok
@kevinakwok28 Feb 2022
This is so wild. bellingcat.com/resources/202…

Radar Interference Tracker: A New Open Source Tool to Locate Active Military Radar Systems -...

Many military radars interfere with open source satellite imagery when they're turned on. A new tool lets anyone monitor when and where these radars are deployed.

bellingcat.com
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Speaking of speeding up Python with @numba_jit, I tried using stencils + @CuPy_Team this past month for MCMC. As someone who’s really only ever coded in Python, this is a match made in heaven
azul (she/her)
@azulgarza_22 Feb 2022
I'm thrilled to announce that we're releasing the fastest #autoarima implementation for #Python today! 😍 It is a mirror implementation of @robjhyndman's #autoarima (R) and it is optimized using @numba_jit. It is 20x faster than pmdarima and @MetaAI's Prophet. 😎 🧵 @nixtlainc
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See here for an example: gist.github.com/mrocklin/927…

numba-cuda-stencil.ipynb

GitHub Gist: instantly share code, notes, and snippets.

gist.github.com
Guess where?
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Jonathan Lindbloom retweeted
NASAEarthdata
@NASAEarthData17 Feb 2022
Announcing Webinar 2/28: SAR Data in Python- Get to Know the ASF Search Module Join us for an introductory webinar to learn how to use asf_search, a new #Python library for search and discovery of #SAR data, created by the NASA #ASFDAAC. To register: go.nasa.gov/35aFrwg
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The Starry Night Cameraman, brought to you by a misguided bayesian inference
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Fixed it
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