Shared Visual Representations in Human & Machine Intelligence
2019 NeurIPS Workshop @ Vancouver Convention Center. Vancouver, Canada
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.
Please see the About page for a more detailed description of the motivation of the workshop.
Invited Speakers & Panelists
Rising Stars Travel Grant recipients (List of young promising graduate/undergraduate* researchers who will be attending the workshop and have had their Registration fees waived)
Judy Borowski (Machine Learning @ Universität Tübingen)
Nikhil Parthasarathy (Neural Science @ NYU)
Jacob Prince* (Psychology @ CMU & Harvard)
Christian Bueno (Mathematics @ UC Santa Barbara)
DeepMind Travel Grant recipients
Judy Borowski (Universität Tübingen)
Chaitanya Ryali (UC San Diego)
Apple Travel Grant recipients
Sophia Sanborn (UC Berkeley)
Ruairidh Battleday (Princeton)