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Simon Prince Profile
Simon Prince

@SimonPrinceAI

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Professor of Computer Science, University of Bath

Toronto, Ontario
Joined July 2019
Don't wanna be here? Send us removal request.
@SimonPrinceAI
Simon Prince
2 years
Are you (or is someone you know) teaching AI / ML / Deep Learning this year? My forthcoming book (freely available at will save you a lot of time. This thread will show you why.
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@SimonPrinceAI
Simon Prince
21 days
This year, I've been writing a new series of articles on ODEs and SDEs for machine learning (suitable for people with zero experience of differential equations). You can find the most recent article (on closed-form solutions for ODEs) here:.
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@SimonPrinceAI
Simon Prince
21 days
Last year I wrote seven tutorials for @RBCBorealis on infinite-width neural networks. Topics included the neural tangent network, Bayesian neural networks and Neural Network Gaussian processes. Includes working code and many novel figures.
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@SimonPrinceAI
Simon Prince
25 days
Wow. Understanding Deep Learning has now been downloaded half a million times. Thank you so much everyone! I was overjoyed when it hit 100k so this is completely mindblowing. I'm so thrilled that people are finding it useful.
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@SimonPrinceAI
Simon Prince
2 months
My friend @TylerJohnMills is looking for collaborators to work on the ARC-AGI competition. This benchmark is interesting and encourages creative approaches to AI. Tyler helped me with my book and would be a fun person to work with. Get in touch directly if you are interested.
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@SimonPrinceAI
Simon Prince
3 months
If you are in the US and are considering buying a hard copy of Understanding Deep Learning, then it is currently available at 37% off on Amazon, for a very reasonable USD 56.99.
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@SimonPrinceAI
Simon Prince
3 months
RT @RBCBorealis: 👋 CALLING ALL STUDENTS! @RBCBorealis is excited to announce our 2025 Fall Technical #Coop Program. This is your chance to….
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@SimonPrinceAI
Simon Prince
4 months
Exciting news! @TravisLacroix (who co-wrote the chapter on ethics in Understand Deep Learning) has a new book out "AI and Value Alignment". Recommended reading for anyone serious about ethics and AI. Details at:. Buy it here: .
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@SimonPrinceAI
Simon Prince
4 months
RT @RBCBorealis: 👋 Work with us! At @RBCBorealis, we are at the forefront of #AI and #data. We build products and #technologies that shape….
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@SimonPrinceAI
Simon Prince
5 months
Here is part III of my series for @RBCBorealis on ODEs and SDEs in machine learning. This article develops methods for solving first-order ODEs in closed form; we divide ODEs into different families and develop approaches to solve each family.
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@SimonPrinceAI
Simon Prince
5 months
Here's the 2nd part of my series of articles on ODEs and SDEs in ML for @RBCBorealis. The article describes ODEs, vector ODEs, and PDEs and categorizes ODEs by how their solutions are related. It also describe conditions for an ODE to have a solution.
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@SimonPrinceAI
Simon Prince
5 months
I'm starting a series of articles on ODEs and SDEs in ML for @RBCBorealis. I'll describe ODEs and SDEs without assuming prior knowledge and present applications including neural ODEs, and diffusion models. Part I: Follow for parts II and III.
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@SimonPrinceAI
Simon Prince
5 months
These blogs for @RBCBorealis.consider infinite-width networks from 4 viewpoints. We use gradient descent or a Bayesian approach, and focus on either the weights or output function. This leads to the Neural Tangent Kernel, Bayesian NNs and NNGPs. Enjoy!.
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@SimonPrinceAI
Simon Prince
6 months
Learning or teaching from my book (? I have now added the complete bibfile (which is accurate and took ages to make) and the LaTeX for all of the equations (helpful if you are making slides).
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@SimonPrinceAI
Simon Prince
6 months
How I'd learn ML in 2025. . (Me too) 😁.
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@SimonPrinceAI
Simon Prince
7 months
@RBCBorealis Main blog: Background info on Gaussian processes:
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@SimonPrinceAI
Simon Prince
7 months
Tutorial 4 of 4 on Bayesian methods in ML for @RBCBorealis concerns Neural Network Gaussian Processes (links in comments). Think your network might perform better if you increased the width? NNGPs are networks with INFINITE width! Includes code to train and run them.
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@SimonPrinceAI
Simon Prince
7 months
Extremely kind words from @justinskycak about "Understanding Deep Learning". Justin himself has a host of useful resources for learning math for ML (see the links in his post) and an interesting summary of the science of learning. See
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@SimonPrinceAI
Simon Prince
8 months
I'm staggered to find that "Understanding Deep Learning" ( has been downloaded >400,000 times. Thanks all for your support (especially those who bought it). I'm staying on X for now, but new blogs will also be found on other platforms if you are not.
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@SimonPrinceAI
Simon Prince
8 months
Blog 3 of 4 on Bayesian methods in ML for @RBCBorealis concerns Bayesian Neural Networks (i.e., Bayesian methods for NNs from a parameter-space perspective):. Parts 1 and 2 (linked in article) introduced Bayesian methods. Coming soon in part 4: NNGPs
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@SimonPrinceAI
Simon Prince
10 months
This is an interesting idea. Reprints of the most important AI papers, together with a discussion and sometimes even comments from the original authors. If your work isn't being cited much, you might want to consider what they all have in common. .
@jgvfwstone
James V Stone
10 months
NEW BOOK: The Artificial Intelligence Papers: Original Research Papers With Tutorial Commentaries. Table of Contents and Chapter 1: "An intellectual string of pearls.'' Karl Friston, FRS.
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