London born, and NYC based Machine Learning Engineer at @meta. Particle physicist in a former life working on the @novaexperiment. He/him.
New York City
Joined November 2011
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I’m excited to announce that my Review has just been published in Nature! It represents an attempt to describe the unique challenges and opportunities at the thriving intersection of machine learning and particle physics:
rdcu.be/3ROR – at Manhattan, NY
Alexander retweeted
We're happy to share that @TmlrOrg recently accepted our paper on "Efficient CDF Approximations for Normalizing Flows" by Chandramouli Sastry, Andreas Lehrmann, @marcusabrubaker and @Alex_Radovic. You can read it here: bit.ly/3TxaTcL.
#CDF #normalizingflows #ML
From my time at @BorealisAI, written with a team of excellent coauthors and former colleagues. I'm really quite proud of our work, and I'm delighted to see it find such a good home.
Efficient CDF Approximations for Normalizing Flows
Chandramouli Shama Sastry, Andreas Lehrmann, Marcus A Brubaker, Alexander Radovic
openreview.net/forum?id=Lnjc…
Alexander retweeted
Efficient CDF Approximations for Normalizing Flows
Chandramouli Shama Sastry, Andreas Lehrmann, Marcus A Brubaker, Alexander Radovic
openreview.net/forum?id=Lnjc…
Open to all undergrads in Canada, it would be great to see some physics undergrads apply!
📣Calling all Undergrads! Let’s SOLVE it, our new mentorship program for students, aims to help you solve problems in your communities using AI. Bring us your best ideas. Let's do this! Apply: bit.ly/2TgLDNC
#AI #ML #Students #DataScience #Diversity #Canada
A great read, and really makes me want to find a good molecular biology textbook!
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Alexander retweeted
I'm thrilled that our Machine Learning for Physical Sciences #NeurIPS2020 workshop proposal was accepted! Last year we had a great turnout and fantastic talks - check out the #ML4PS hashtag. New to team: @adjiboussodieng @iamstarnord @glouppe @zdeborova ml4physicalsciences.github.i…
ALT photos of website, organizers, and steering committee members
Heartbreaking, although perhaps not that surprising in hindsight. I think we'll be dissecting how this pandemic cracked open the fault lines in our society for decades.
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This might be the last physics paper I directly contributed to? A strange but very peaceful feeling. I look forward to seeing where this work goes next, the team still working on ML at DUNE is really excellent.
Want to see what a #deepLearning approach based on #ConvolutionalNeuralNetwork can do to provide highly efficient and pure selections of #electronNeutrino and #muonNeutrino? 🥳 Check out our latest paper on arXiv:2006.15052
arxiv.org/abs/2006.15052
"Criminality" prediction is one of the lines of ml "research" I find most disturbing. Please consider cosigning, particularly if you're in the field.
I signed this letter.
The main purpose of this letter is to demand that Springer withdraw the publication of a paper from Harrisburg University entitled "A Deep Neural Network Model to Predict Criminality Using Image Processing”.
Letter: medium.com/@CoalitionForCrit…
1/2
Alexander retweeted
OK, so, I've seen a lot of the "NASA detects parallel universe" stuff going around
I've spent the last ~2 years of grad school investigating these detections, and wanted to provide a bit of background and clarification
(1/n)
Alexander retweeted
In our preprint “The large learning rate phase of deep learning: the catapult mechanism" arxiv.org/abs/2003.02218, we show that the choice of learning rate (LR) in (S)GD separates deep neural net dynamics into two sharply distinct types (or "phases", in the physics sense). (1/n)
Alexander retweeted
A nice article by @Alex_Danco that explains how academic research really works, how it became the way it is, and how Twitter might play an important role in disrupting it.
Good read for non-academics to understand incentive structures of the institution.
danco.substack.com/p/can-twi…
Alexander retweeted
Our review, focused on some recent efforts at this interface and hopefully accessible to a non-ML science audience.
1/ Our new paper in @AnnualReviews of Condensed Matter Physics on “Statistical Mechanics of #DeepLearning” with awesome collaborators @Stanford and @GoogleAI : @yasamanbb @kadmonj Jeff Pennington @sschoenholz @jaschasd
web: annualreviews.org/doi/abs/10…
free: annualreviews.org/eprint/B3F…
Alexander retweeted
Did you know that other than the REINFORCE estimator and reparametrization trick, there is another Monte Carlo gradient estimator called the "measure-valued gradient estimator"? Check out my new blog post: bochang.me/blog/posts/measur…
Alexander retweeted
IMPORTANT: Students at UCSC are on strike. They're campaigning for a small (and urgently needed) Cost of Living Adjustment, or COLA. UCSC has responded with armed police and threats of deportation and firings.
Follow: @payusmoreucsc
Donate: tinyurl.com/paythemmoreucsc
Alexander retweeted
Happy to share our work on using generative models as surrogates of non-differentiable simulators to enable (approximate) gradient based optimization. arxiv.org/abs/2002.04632
Alexander retweeted
ML Fairness Gym is a set of components for building simple simulations that explore the potential long-run impacts of deploying machine learning-based decision systems in social environments, based on OpenAI Gym interface.
github.com/google/ml-fairnes…
