Yue Qin
115 posts

Yue Qin
@fullhey2
Zhejiang University, Master of Physical Oceanography, Machine learning
Zhejiang Bergabung Nisan 2020
276 Mengikuti30 Pengikut

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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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

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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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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… ∀.
GIF
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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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💫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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Looking for a stats or applied maths PhD? There are 2 great PhD programmes at Imperial that are currently welcoming applications: "Mathematics for our Future Climate" and "Statistics and Machine Learning." Find out more here!...
mfccdt.ac.uk/recruitment-pa…
statml.io/index.php/how-…
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> 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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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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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…

YouTube
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#OceanOpportunities 25 PhD positions at the Alfred Wegener Institute nf-pogo-alumni.org/opportunities/…
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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…

YouTube
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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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