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Swaroop Guntupalli proslijedio/la je Tweet
You'd think a generative model should answer different queries but deep learning models like VAEs are trained to answer just one type of query! We introduce a method called query-training that creates an inference network that can answer novel query types. https://openreview.net/pdf?id=rJeoKJ3NKr …pic.twitter.com/SVR0kxpwQJ
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Swaroop Guntupalli proslijedio/la je Tweet
How is it even possible, now that "AI has taken over", that I buy a washing machine and everything starts recommending me more washing machines? (don't get me wrong: it is a comforting feeling that, outside the movies, not much has happened since Eliza)
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Swaroop Guntupalli proslijedio/la je Tweet
We show that a singular principle of variable-order sequence learning in a structured model can explain cognitive maps phenom: spatial maps, transitive inference, temporal order, hierarchical planning, remapping etc. -- all important for AI & neuroscience. https://www.biorxiv.org/content/10.1101/864421v1 …pic.twitter.com/k8guF87lEB
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Swaroop Guntupalli proslijedio/la je Tweet
Great interview, in which the man
@yarikoptic himself explains how he manages to get an infinite amount of work done in the same finite time that the rest of us have ;-) thx@vsoch !https://twitter.com/vsoch/status/1202625098882007040 …
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Swaroop Guntupalli proslijedio/la je Tweet
It also learns a lossy compressed graph representation of the underlying sequences. Closely related to our 1st paper on cognitive maps as higher-order sequences.
@rvrikhye@swaroopgj#CCN2019https://twitter.com/vicariousai/status/1166427035423522816?s=20 …
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Insightful commentary from
@dileeplearning https://arxiv.org/abs/1909.01561Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Swaroop Guntupalli proslijedio/la je Tweet
Our
#CCN2019 paper proposes a new model for cognitive maps in the hippocampus which involves learning higher-order graphs of event sequences. It can explain flexible planning, route-dependence of place cells, and subsumes successor representations. https://www.biorxiv.org/content/10.1101/745950v1?rss=1 …pic.twitter.com/KASM6l6RBK
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Swaroop Guntupalli proslijedio/la je Tweet
1/ New in
@sciencemagazine w/@KarlDeisseroth lab: https://science.sciencemag.org/content/early/2019/07/17/science.aaw5202 …: new opsin + multi-photon holography to image ~4000 cells in 3D volumes over 5 cortical layers while also stimulating ~50 neurons to directly drive visual percepts; data analysis and theory reveal…pic.twitter.com/Wy1PLvrzz6
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Swaroop Guntupalli proslijedio/la je Tweet
Thread about our new paper on learning the structure of variable order sequences. Imposing a biologically-inspired sparsity structure alleviates the credit diffusion problem in HMMs! Also relevant for neuroscience... (1)
@vicariousai https://arxiv.org/abs/1905.00507 pic.twitter.com/K2iXJmM6XW
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Swaroop Guntupalli proslijedio/la je Tweet
If yuor laugnage moedl cnnaot raed tihs, it mgiht not be vrey dnagorues
. See our paper on learning graphs that can model higher-order sequences and deal with uncertainty. https://arxiv.org/abs/1905.00507 pic.twitter.com/b1bHNZ7Om4
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Swaroop Guntupalli proslijedio/la je Tweet
A thought is a program! Check out our blog to see how we are building a cognitive architecture towards AGI. Also included: code, data, and a free link to our recent Science Robotics paper on concept learning.https://www.vicarious.com/2019/01/18/a-thought-is-a-program/ …
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Swaroop Guntupalli proslijedio/la je Tweet
Mini thread about the cognitive science and neuroscience inspirations behind our new paper in which we learn concepts as 'cognitive programs' on a 'visual cognitive computer'. http://robotics.sciencemag.org/content/4/26/eaav3150 …pic.twitter.com/HxIH3ZQdPE
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Swaroop Guntupalli proslijedio/la je Tweet
Instead of relying on a list or rules, a new computational framework for learning lets robots come up with their own concepts by detecting abstract differences in images and then recreating them in real life: http://bit.ly/2RyGw9c pic.twitter.com/pu8nwPnh7S
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Swaroop Guntupalli proslijedio/la je Tweet
Our concept-learning work is now published in Science Robotics! Checkout this very nice video that Science made to explain the paper.https://twitter.com/NewsfromScience/status/1085648047349030912 …
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Swaroop Guntupalli proslijedio/la je Tweet
Our new paper learns concepts as programs on a 'visual cognitive computer', showing zero-shot task-transfer on robots, and strong generalization. We bring cogsci ideas about perceptual symbol systems and image schemas into the realm of machine learning. https://arxiv.org/abs/1812.02788 pic.twitter.com/wkKrPe8CZA
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Swaroop Guntupalli proslijedio/la je Tweet
What a gift! Ramanujan’s papers, now online.https://twitter.com/TrinCollLibCam/status/1033979998233927680 …
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Swaroop Guntupalli proslijedio/la je Tweet
Moore's law sputtering to an end. Now is the time for new architectures and creativity!https://spectrum.ieee.org/nanoclast/semiconductors/devices/globalfoundries-halts-7nm-chip-development …
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Swaroop Guntupalli proslijedio/la je Tweet
New paper with
@mafeilong,@swaroopgj, and@haxbylab! Hyperalignment factors out idiosyncrasies in functional–anatomical correspondence, revealing individual differences in fine-grained functional architecture otherwise obscured by anatomical normalization http://doi.org/10.1016/j.neuroimage.2018.08.029 …https://twitter.com/mafeilong/status/1039580726633660416 …
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Swaroop Guntupalli proslijedio/la je Tweet
Checkout our CCN-18 papers! (1) RCN-derived circuits suggest precise functional roles for feed-forward, feedback, and lateral connections, and for the thalamus. (2) RCN can explain multiple visual phenomena including two well-known illusions.
#CCN18#microcircuitspic.twitter.com/HfoKoHIscT
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Swaroop Guntupalli proslijedio/la je Tweet
Here are the links to our CNN-18 papers: Cortical Microcircuits from a Generative Vision Model: https://www.biorxiv.org/content/early/2018/08/05/379313 … Explaining Visual Cortex Phenomena using Recursive Cortical Network:https://www.biorxiv.org/content/early/2018/07/30/380048 …
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