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Simon Kornblith proslijedio/la je Tweet
To anyone in the whisker field: this is the greatest thing ever.https://openreview.net/forum?id=1uOTdL2H9i …
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Just ate "The Apple of Big Dreams"
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@carlesgelada@jacobmbuckman Perhaps this is the prior you're looking for. (Obviously, a fully Bayesian treatment would marginalize over the distribution of distributions of weight distributions instead of using EM.)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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"Simplifying Neural Network Soft Weight-sharing Measures by Soft Weight-measure Soft Weight Sharing" (Pearlmutter, 1994) https://www.tandfonline.com/doi/abs/10.1080/09540099408915712?journalCode=ccos20 …pic.twitter.com/178U8ps9ez
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Simon Kornblith proslijedio/la je Tweet
This photo of fried chicken really hits home effects of context (grill...floor) on object recognition (dogs)pic.twitter.com/AjVVzTe430
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Simon Kornblith proslijedio/la je Tweet
The winning entry of a Kaggle machine learning competition hacked the website to get the test labels, buried and encoded them into a "private external dataset", reloaded them during pre-processing, and added noise to not get a performance of 100%. This is pretty sad.https://twitter.com/tunguz/status/1215655284422496257 …
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Simon Kornblith proslijedio/la je Tweet
Critics: AI can't even beat a human at a simple game Researchers: no it's totally great at games now C: okay but not Go R: ya C: okay but it can't produce coherent sentences R: well, actually... C: whatever, it can't wiggle its ears like this
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Simon Kornblith proslijedio/la je Tweet
Our analysis suggests that a large portion of choice-correlated variability in MT is in a subspace NOT aligned with the sensory encoding and lives in the *null-space*!pic.twitter.com/KfU7sNcHII
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Simon Kornblith proslijedio/la je Tweet
With judicious refinement of modern tricks, and scale, we can push SOTA (on VTAB, ImageNet, Cifar, etc.) using classic transfer learning, without excessive complexity. Works surprisingly well even with <=10 downstream examples per class.https://twitter.com/giffmana/status/1214240746095730688 …
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Simon Kornblith proslijedio/la je Tweet
What gems.
@skornblith brought me the elusive@alizaelk art zines from Toronto. The one on the right is about the Steve jobs fashion dataset "There is a little hot Steve jobs in all of us" lolpic.twitter.com/Dsyqgnt9Mk
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Simon Kornblith proslijedio/la je Tweet
Come to our poster (w/
@skornblith and@quocleix) today Wednesday at#Neurips2019 to learn how to improve the accuracy of hard attention models for vision. (Poster #70 10:45am-12:45pm East Exhibition hall B + C)Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Simon Kornblith proslijedio/la je Tweet
if y'all r lookin for somethin to read while walking around Vancouver, check out my newest paper: "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One" https://arxiv.org/abs/1912.03263 with
@kcjacksonwang@jh_jacobsen@DavidDuvenaud@Mo_Norouzi@kswerskPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
@ NeurIPS to support: “Saccader: Improving Hard Attention Models for Vision” Wed w/
@gamaleldinfe@quocleix “When Does Label Smoothing Help?” spot
Thu w/@rafaelrmuller@geoffreyhinton “Exploring CNN Inductive Biases: Shape vs Texture”@svrhm2019 wrkshp w/@khermann_ Come say hi!Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Simon Kornblith proslijedio/la je Tweet
Infinite width networks (NNGPs and NTKs) are the most promising lead for theoretical understanding in deep learning. But, running experiments with them currently resembles the dark age of ML research before ubiquitous automatic differentiation. Neural Tangents fixes that.https://twitter.com/sschoenholz/status/1202988151569973248 …
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Simon Kornblith proslijedio/la je Tweet
[
#SVRHM2019 Workshop Paper Preview] Hermann et al. show that despite a texture bias, CNNs learn shape distinctions faster / with less data. To increase shape bias, remove random-crop augmentation and increase learning rate / weight decay! Full papers at http://svrhm2019.com pic.twitter.com/BwoacxBONW
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Simon Kornblith proslijedio/la je Tweet
To recap, the current AI war is no longer the age-old war btw symbolists and connectionists, but btw those who decry that the war is still ongoing and those saying that there's no longer one. But don't quote me. I'm not willing to start a war on whether there is a war about a warhttps://twitter.com/MattiaRigotti/status/1201169734802300930 …
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Simon Kornblith proslijedio/la je Tweet
Excited to share new work, in collaboration with
@skornblith, investigating the texture bias in ImageNet-trained CNNs: https://arxiv.org/abs/1911.09071 .pic.twitter.com/ZuC74vrghH
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Simon Kornblith proslijedio/la je Tweet
Here's a crazy idea. All the authors got free links to share to their COiN articles (valid until mid December). Why not put them in one place (perhaps as responses to this tweet?)
@bingbrunton@andpru@NeuroNaud@NeuralCodeUMD@srinituraga@EngelTatiana https://www.sciencedirect.com/journal/current-opinion-in-neurobiology/vol/58/suppl/C …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Simon Kornblith proslijedio/la je Tweet
So grateful for
@skornblith 's colab on CKA. It seems obvious in retrospect but I hadn't considered the equivalence of calculating similarities based on examples and based on features. My experiments are so much faster now...
https://twitter.com/skornblith/status/1138859179165093888 …pic.twitter.com/SJXWjXiLUf
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. In past lives, I was a neuroscientist