Yue Qin

115 posts

Yue Qin

Yue Qin

@fullhey2

Zhejiang University, Master of Physical Oceanography, Machine learning

Zhejiang شامل ہوئے Nisan 2020
276 فالونگ30 فالوورز
Alistair MacLeòid
Alistair MacLeòid@Al_Mc72·
Waited in today for a delivery from @RoyalMail because I knew it wouldn’t fit the letterbox. Between 11:15 and 15:15 they said. Fucking 15:50 get an email “sorry we couldn’t deliver”. You had all fucking day! Who are you fucking Evri?!?
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Razia Aliani
Razia Aliani@RaziaAliani·
Read this paper to know how to 'actually' read a paper! I've highlighted the key points -> now this 10 min read of 3-pass apprach will change your paper reading technique for good! 𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: — First Pass (5-10 minutes) Quick scan for bird's-eye view — Second Pass (up to 1 hour) Read with greater care —>> Third Pass below ⬇️ 💬 𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗽𝗮𝗽𝗲𝗿𝘀? 1/2
Razia Aliani tweet media
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Xiaoxu Tian
Xiaoxu Tian@xiaoxu_tian·
ML weather models like GraphCast & NeuralGCM show promise in weather forecasting, but can they be used for data assimilation? Our study looks into their tangent linear & adjoint models, finding challenges in robustness & unphysical noise. 🌦️ #AI #NWP arxiv.org/abs/2411.14677
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Mushtaq Bilal, PhD
Mushtaq Bilal, PhD@MushtaqBilalPhD·
Finding relevant papers for literature review takes a lot of time. So, MIT researchers built Undermind, an AI-powered search engine. It can generate well-researched overviews on any topic and is 10-50 times better than Google Scholar. Here's how to use it:
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Michael Pyrcz🌻
Michael Pyrcz🌻@GeostatsGuy·
Many students have trouble understanding #Bayesian #MachineLearning, to help them I coded up Bayesian linear regression with MCMC to sample the posterior from scratch. Then I built out this interactive #Python dashboard with @matplotlib. Vary the number of MCMC samples and watch the transition from burn-in to equilibrium chain. Try it out on #GitHub @ github.com/GeostatsGuy/Da… ∀.
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Patrick Kidger
Patrick Kidger@PatrickKidger·
For those chasing down this rabbithole, I wrote a 'learn JAX as a PyTorch developer' guide a while ago: kidger.site/thoughts/torch… If that's helpful :)
xjdr@_xjdr

This has been and will continue to be my recommendation for anyone in this position. Learn jax and sign up for sites.research.google/trc/about/ Its one of the best things Google has ever done. You can do meaningful research for free, but the learning curve is steep. strap in

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Mushtaq Bilal, PhD
Mushtaq Bilal, PhD@MushtaqBilalPhD·
Limitation of Google Scholar: You can only look up articles with keywords. It doesn't work if you paste a sentence or a paragraph. Sourcely is an AI-powered app that lets you look up papers using whole paragraphs. Here's how to use it:
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Patrick Kidger
Patrick Kidger@PatrickKidger·
💫Fellow scientific computing geeks, here is an example of adaptive mesh refinement in #JAX: gist.github.com/patrick-kidger… I recently heard a claim that this was impossible in JAX due to its lack of dynamic shapes, and decided to prove the naysayers wrong 😄
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Saurabh Kumar
Saurabh Kumar@drummatick·
> Linear Algebra by Prof Gilbert Strang > Probability Theory Prof John Tsitsiklis > Information Theory by David Mackay > Optimization theory by Stanford University > Machine learning by Andrew NG(Stanford course) This is all you need to master ML. Coursework + assignments + course projects and you’ll be better than most people at ML.
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Anita Devineni
Anita Devineni@BrainsExplained·
As we're heading into PhD application season, I wrote a post with advice for applying to grad school, drawing from my experience on admissions committees. Please share with any aspiring PhD students that you know! brains-explained.com/advice-for-app…
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Jason J. Bramburger
Jason J. Bramburger@jbramburger7·
I'm starting a lecture series on partial differential equations which will run over the next few months. Join me! youtube.com/watch?v=YcG1NY…
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Yue Qin
Yue Qin@fullhey2·
Good news: I got my first certificate of reviewing!😆 Bad news: I rejected that manuscript.😅
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Ben Moseley
Ben Moseley@benm_oseley·
We just released our ETH Zürich AI in the Sciences and Engineering Master’s course on YouTube! 📚 Prof. Siddhartha Mishra and I explain PINNs, neural operators, foundation models, neural PDEs, diffusion models, symbolic regression, and more! #AI4Science youtube.com/watch?v=LkKvhv…
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Jousef Murad
Jousef Murad@Jousefm2·
Teaching Neural Network to Solve Navier-Stokes Equations Demonstrating the process of building a physics informed neural network (PINN) to predict the behaviour of vortex shedding using the Navier-Stokes equations. 🌎 Github: github.com/ComputationalD… More Resources👇
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