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Drew Linsley proslijedio/la je Tweet
This really messed with my head for a few minutes before I realisedpic.twitter.com/HiFaDG6DCy
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Drew Linsley proslijedio/la je Tweet
So thrilled to be teaching this class again! Come write your novels w/ me!https://twitter.com/catapultstory/status/1224403478488997891 …
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Drew Linsley proslijedio/la je Tweet
A minimal Turing test (McCoy & Ullman, 2018): “Say one word that convinces us you're human.”pic.twitter.com/ZhPkVQiIxH
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Drew Linsley proslijedio/la je Tweet
My blogpost on how & why we use convolutional neural networks as a model of the visual system is probably the most read thing I've ever written and it's now been expanded & updated into a proper review article, complete with 136 references & 5 new figures! https://arxiv.org/abs/2001.07092 pic.twitter.com/xRqYKptTsF
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Drew Linsley proslijedio/la je Tweet
I am very excited, to finally share this: https://www.nature.com/articles/s41593-019-0576-z … Using a functional
#connectomics approach we uncovered a mechanism for whitening, a fundamental computation that decorrelates neuronal population activity for pattern classification by memory networks.Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Drew Linsley proslijedio/la je Tweet
A new microscope technique shows cells’ fine structure in new detail. The method, developed by Eric Betzig, Harald Hess + colleagues, combines 3D super-resolution fluorescence microscopy and electron microscopy in whole cells. Published today in Science! http://bit.ly/2uWFOIz pic.twitter.com/75emy4ghW0
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Drew Linsley proslijedio/la je Tweet
The petition for SFN to reduce emissions has reopened. 1180 signatures so far. This is a tiny fraction of the number of members. Please consider signing. This is a no brainer.https://twitter.com/SfN_climate/status/1218219156123811846 …
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Drew Linsley proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Drew Linsley proslijedio/la je Tweet
New preprint from the lab: "Individual differences among deep neural network models." https://www.biorxiv.org/content/10.1101/2020.01.08.898288v1 … Work with
@KriegeskorteLab,@HannesMehrer, and Courtney Spoerer.#tweeprint below. 1/7Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Drew Linsley proslijedio/la je Tweet
What are the mechanisms that modulate gain in the
#cortex? Check out this latest Review by@kt_ferguson and@jess_cardin https://go.nature.com/36BoZ3V pic.twitter.com/SJwjK7BJxQ
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Drew Linsley proslijedio/la je Tweet
New paper out! We provide evidence that feedforward convnets (ffCNNs) cannot implement human-like global computations because of their *architecture*, and not merely because of the way they are *trained*.https://www.sciencedirect.com/science/article/pii/S0042698919302299 …
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Drew Linsley proslijedio/la je Tweet
*REMINDER + PLS RT* Our workshop, From Neuroscience to Artificially Intelligent Systems (NAISys), has an abstract deadline of January 10. This Friday!!! But, it's only 1-page, so easy-peasy: https://meetings.cshl.edu/meetings.aspx?meet=NAISYS&year=20 … Please send in ideas for how neuroscience can inform AI!pic.twitter.com/AZNNIUSg0N
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Drew Linsley proslijedio/la je Tweet
also - very nice (+ impressively coordinated) thread by the authors herehttps://twitter.com/SebastianSeung/status/1212846451790880779?s=20 …
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Drew Linsley proslijedio/la je Tweet
Some really fascinating results linking functional characterizations of optically recorded synaptic inputs and EM reconstructions of the synapses to challenge theories of Hebbian learning's role in shaping selectivity in Ferret V1https://www.biorxiv.org/content/10.1101/2019.12.24.887422v1 …
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In sum: (Paper 1) Introduce a deep feedback model exhibits an orientation-tilt illusion and outperforms state-of-the-art vision models in contour detection. (Paper 2) Test the computational role of feedback connections for solving complex visual tasks. See you at ICLR! 17/17
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Our feedback models are also significantly better than leading feedforward DNNs at capturing human decisions on these tasks. The recurrent visual strategies learned by the models are a better fit for human decision making than visual strategies learned by typical DNNs. 16/17pic.twitter.com/J3gYaBCWro
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We train deep feedback models on these tasks, and find a double-dissociation. Horizontal connections are important for leveraging Gestalt, or in this case path tracing. Top-down connections are important for leveraging semantic information, and selecting letters. 15/17pic.twitter.com/3ZXcU5xfT6
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The first dataset is solved with "Gestalt": finding a dot and tracing to the other end of the long path. The second dataset is solved with semantics: recognizing one of the two letters, ignoring the other, and counting the dots on it. 14/17pic.twitter.com/ngdN507GtG
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Feedback connections in visual cortex have broadly been split into local "horizontal" connections and long-range "top-down" connections. We created two datasets to disentangle these connections, both of which ask whether two dots are on the same or different objects. 13/17
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In our other paper, http://bit.ly/iclrdis , we explore a long-standing question in vision science: What are the computational roles of different forms of feedback connections in visual cortex? 12/17pic.twitter.com/2a5sxSUHgL
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