Embedded Files
The goal of the 3rd 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 methodsโespecially deep neural networksโhave 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 self-supervised 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
Invited Speakers & Panelists
Yalda Mohsenzadeh ๐ฎ๐ท
Western University
Department of Computer Science & Brain and Mind Institute
Ruben Coen-Cagli ๐ฎ๐น
Albert Einstein College of Medicine
Department of Systems and Computational Biology
Zoya Bylinskii ๐จ๐ฆ
Adobe Research
Creative Intelligence Lab
Gemma Roig ๐ช๐ธ
Goethe University Frankfurt
Department of Computer Science
Yukiyasu Kamitani ๐ฏ๐ต
Kyoto University & ATR
Department of Information Sciences & Technologies
Maryam Vaziri-Pashkam ๐ฎ๐ท
National Institute of Health
Laboratory of Brain and Cognition
Michelle Greene ๐บ๐ธ
Bates College
Department of Neuroscience
Roland Fleming ๐ฉ๐ช/๐ฌ๐ง
Giessen University
Department of Psychology
Ruth Rosenholtz ๐บ๐ธ
MIT
Computer Science and Artificial Intelligence Lab (CSAIL) & Brain and Cognitive Sciences Department (BCS)
Xavier Boix ๐ช๐ธ/Catalonia
MIT
Brain and Cognitive Sciences Department
Wieland Brendel ๐ฉ๐ช
Universitรคt Tรผbingen & Layer 7AI
International Max Planck Research School for Intelligent Systems
Stรฉphane Deny ๐ซ๐ท /๐บ๐ธ/๐ซ๐ฎ/
Facebook AI Research & Aalto University
Kohitij Kar ๐ฎ๐ณ
MIT
McGovern Institute for Brain Research
Tiago Marques ๐ต๐น
MIT
McGovern Institute for Brain Research
Chaz Firestone ๐จ๐ฆ
Johns Hopkins University
Department of Psychological and Brain Sciences & Department of Philosophy
Donsuk Lee ๐ฐ๐ท
Indiana University
Informatics and Cognitive Sciences Department
Andy Keller ๐บ๐ธ
University of Amsterdam
Machine Learning Department
Bhavin Choksi ๐ฎ๐ณ
French National Center for Scientific Research (CNRS)
Brain and Cognition Research Center (CerCO)
Tushar Arora ๐ฎ๐ณ
University of Tokyo
International Research Center for Neurointelligence (IRCN)
Organizers
Organizers
Arturo Deza ๐ต๐ช
MIT
Center for Brains, Minds and Machines
Apurva Ratan Murty ๐ฎ๐ณ
MIT
McGovern Institute for Brain Research
Thomas Griffiths ๐บ๐ธ/๐ฌ๐ง/๐ฆ๐บ
Princeton University
Departments of Computer Science and Psychology
Sponsors
Sponsors
MIT Center for Brains, Minds and Machines (CBMM)
National Science Foundation (NSF)
NVIDIA
Facebook Reality Labs (FRL)
MIT Quest for Intelligence
Brain Score Initiative
Adobe Research
This material/activity is funded, in full or in part, by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Google Sites
Report abuse