Joined October 2011
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6 Dec 2022
Did not expect to be role-playing with a GPU this evening.
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6 Dec 2022
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Mike retweeted
25 Nov 2020
Excited to share our @UofT & @VectorInst work "Emergent Road Rules in Multi-Agent Driving Environments" w/ @PhilionJonah, Andrew Liao & @FidlerSanja. Paper: arxiv.org/abs/2011.10753 Project Page: fidler-lab.github.io/social-… Code: github.com/fidler-lab/social… [1/5]
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4 Oct 2020
“I can’t live two hours without my ID, he said to himself. I don’t even dare walk out of the lobby of this rundown hotel and onto the public sidewalk. They’ll assume I’m a student or teacher escaped from one of the campuses.” – Philip K. Dick
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4 Oct 2020
“He knew that at one time she had been illegally married to a student commune leader, and that for one year she had lived in the rabbit warrens of Columbia University, along with all the smelly, bearded students kept subsurface lifelong by the pols and the nats. ...
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4 Oct 2020
"The police and the national guard, who ringed every campus, keeping the students from creeping across to society like so many black rats swarming out of a leaky ship.”
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Mike retweeted
The Imperial College epidemic simulation code that I helped a little on is now public: github.com/mrc-ide/covid-sim I am a strong proponent of public code for models that may influence policy, and while this is a "release" rather than a "live" depot, it is a Good Thing.
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17 Mar 2020
Imperial College paper that has informed UK pandemic policy. Well-explained exploration of some of the tradeoffs involved imperial.ac.uk/media/imperia…

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Mike retweeted
I am at #NeurIPS. If anyone else is at NeurIPS and wants to chat about #julialang or automatic differentiation (in any language). Poke me here.
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Mike retweeted
18 Oct 2019
How do you differentiate a curried function? What’s the tangent space of a function type? Explained in our new paper: “The Differentiable Curry” openreview.net/forum?id=ryxu…
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Mike retweeted
I hope this is part of a trend exploring more and more in this direction. As @karpathy said, "gradient descent is a better programmer than you": arxiv.org/abs/1907.07587
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Mike retweeted
24 Jul 2019
If you want to know more about Differentiable Rendering and how we used it on the @DuckietownAI Platform do checkout my #juliacon talk on "Differentiable Rendering and its Applications in Deep Learning" bit.ly/2Zjm9wV
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Mike retweeted
"RayTracer.jl: A Differentiable Renderer that supports Parameter Optimization for Scene Reconstruction" is the #1 paper on Arxiv today in graphics. Congrats @avikpal1410. See it at -> assert.pub/arxiv/cs/cs.gr and assert.pub/papers/1907.07198. Please retweet.

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Mike retweeted
Interesting paper! Tensorflow 2.0 and PyTorch 1.1 already pushed the language to the limits of what it can do. As Julia and Swift mature their support for #deeplearning, we may need to switch buff.ly/320IH76

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Mike retweeted
Today we start! "Advances and Challenges in ML Languages" #ACMLL, with TF tutorials by @dustinvtran and @pearce_ and Stan by @dan_p_simpson Tomorrow talks by @lawrennd @ArnaudDoucet1 @StatModeling @Tkaraletsos @MikeJInnes and more Schedule: yebai.github.io/mll-workshop… … …

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Mike retweeted
Just came across this in the @JuliaLanguage #DeepLearning library @FluxML 😂
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Mike retweeted
When fitting a PDE with a neural network in #julialang, if you progress=true in the timestepping, you get a nested progress bar that tells you how the current PDE solve is doing, with an outer one for how the neural net training is doing. Neural PDEs on #CFD with DiffEqFlux.jl
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Mike retweeted
That’s fine but does not make Swift the first language to support differential programming. As far as I understand Swift does not yet support `if` statements. Meanwhile #JuliaLang is speeding up ML by 100x using DP on arbitrary code: fluxml.ai/2019/03/05/dp-vs-r…

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6 Mar 2019
I'll be speaking at the Machine Learning Languages conference in Cambridge this May. Looks like it will be a great event; folks doing ML in Julia should definitely submit posters! bigdata.cam.ac.uk/events/adv…

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