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

Fri Dec 13th 08:00 AM -- 07:00 PM @ West 220 - 222
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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.

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08:50 AM Opening Remarks <span> <a href="#"></a> </span> Arturo Deza, Joshua Peterson, Apurva Ratan Murty, Tom Griffiths
09:00 AM Predictable representations in humans and machines (Talk) Olivier Henaff
09:25 AM What is disentangling and does intelligence need it? (Talk) Irina Higgins
09:50 AM Coffee Break (Break)
10:10 AM A "distribution mismatch" dataset for comparing representational similarity in ANNs and the brain (Talk) Wu Xiao
10:35 AM Feathers, wings and the future of computer vision research (Talk) Bill Freeman
11:00 AM Taxonomic structure in learning from few positive examples (Talk) Erin Grant
11:25 AM CIFAR-10H: using human-derived soft-label distributions to support more robust and generalizable classification (Talk) Ruairidh Battleday
11:50 AM Making the next generation of machine learning datasets: ObjectNet a new object recognition benchmark (Talk) Andrei Barbu
12:15 PM The building blocks of vision (Talk) Michael Tarr
02:00 PM Poster Session <span> <a href="#"></a> </span>
Ethan Harris, Tom White, Oh Hyeon Choung, Takashi Shinozaki, Dipan Pal, Katherine Hermann, Judy Borowski, Camilo Fosco, Chaz Firestone, Vijay Veerabadran, Ben Lahner, Chaitanya Ryali, Fenil Doshi, Pulkit Singh, Sharon Zhou, Michel Besserve, Michael Chang, Anelise Newman, Mahesan Niranjan, Jonathon Hare, Daniela Mihai, Marios Savvides, Simon Kornblith, Christina M Funke, Aude Oliva, Virginia R de Sa, Dmitry Krotov, Colin Conwell, George Alvarez, Alex Kolchinski, Shengjia Zhao, Mitchell Gordon, Michael Bernstein, Stefano Ermon, Arash Mehrjou, Bernhard Schölkopf, JD Co-Reyes, Michael Janner, Jiajun Wu, Josh Tenenbaum, Sergey Levine, Yalda Mohsenzadeh, Zhenglong Zhou
03:00 PM Q&A from the Audience. Ask the Grad Students (Discussion Panel) Erin Grant, Ruairidh Battleday, Sophia Sanborn, Nadine Chang, Nikhil Parthasarathy
03:30 PM Object representation in the human visual system (Talk) Talia Konkle
03:55 PM Cognitive computational neuroscience of vision (Talk) Nikolaus Kriegeskorte
04:20 PM Perturbation-based remodeling of visual neural network representations (Talk) Matthias Bethge
04:45 PM Local gain control and perceptual invariances (Talk) Eero Simoncelli
05:10 PM Panel Discussion: What sorts of cognitive or biological (architectural) inductive biases will be crucial for developing effective artificial intelligence? (Discussion Panel) Irina Higgins, Talia Konkle, Matthias Bethge, Nikolaus Kriegeskorte
06:00 PM Concluding Remarks & Prizes Ceremony (Concluding Remarks) Arturo Deza, Joshua Peterson, Apurva Ratan Murty, Tom Griffiths
06:10 PM Evening Reception (Reception)

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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