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Shared Visual Representations in Human and Machine Intelligence
Arturo Deza · Joshua Peterson · Apurva Ratan Murty · Tom Griffiths

Fri Dec 13 08:00 AM -- 07:00 PM (PST) @ West 220 - 222
Event URL: http://www.svrhm2019.com/ »

The goal of the Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop is to disseminate relevant, parallel findings in the fields of computational neuroscience, psychology, and cognitive science that may inform modern machine learning methods.

In the past few years, machine learning methods—especially deep neural networks—have widely permeated the vision science, cognitive science, and neuroscience communities. As a result, scientific modeling in these fields has greatly benefited, producing a swath of potentially critical new insights into human learning and intelligence, which remains the gold standard for many tasks. However, the machine learning community has been largely unaware of these cross-disciplinary insights and analytical tools, which may help to solve many of the current problems that ML theorists and engineers face today (e.g., adversarial attacks, compression, continual learning, and unsupervised learning).

Thus we propose to invite leading cognitive scientists with strong computational backgrounds to disseminate their findings to the machine learning community with the hope of closing the loop by nourishing new ideas and creating cross-disciplinary collaborations.

See more information at the official conference website: https://www.svrhm2019.com/
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Author Information

Arturo Deza (Harvard University)
Joshua Peterson (Princeton University)
Apurva Ratan Murty (Massachusetts Institute of Technology)
Tom Griffiths (Princeton University)

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