Featured news

Graphic of someone tracking the motion of billiard balls
How we determine who’s to blame [MIT News]
October 17, 2017
Before assigning responsibility, our minds simulate alternative outcomes, study shows. Anne Trafton | MIT News Office October 17, 2017 “What’s really cool about eye tracking is it lets you see things...
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Seminars + events

Klaus-Robert Müller
Brains, Minds + Machines Seminar Series: Machine learning and AI for the science...
November 17, 2017 - 2:00 pm
MIT Building 46-3002 (Singleton Auditorium)
Klaus-Robert Müller, Technische Universität Berlin
Abstract: In recent years, machine learning (ML) and artificial intelligence (AI) methods have...
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CBMM spotlight

Georgios Evangelopoulos: Speech Recognition
Georgios Evangelopoulos: Speech Recognition
Associated Research Thrust:
Theoretical Frameworks for Intelligence
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Highlighted publications

T. Gerstenberg, Peterson, M. F., Goodman, N. D., Lagnado, D. A., and Tenenbaum, J. B., “Eye-Tracking Causality”, Psychological Science, vol. 73, 2017...
M. J. Arcaro, Schade, P. F., Vincent, J. L., Ponce, C. R., and Livingstone, M. S., “Seeing faces is necessary for face-domain formation”, Nature Neur...
CBMM Memo No:
069
A. Volokitin, Roig, G., and Poggio, T., “Do Deep Neural Networks Suffer from Crowding?”. 2017.
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Featured video

Embedded thumbnail for Dimensionality Reduction for Matrix- and Tensor-Coded Data [Part 1]
Dimensionality Reduction for Matrix- and Tensor-Coded Data [Part 1]
Alex Williams, Stanford University
In many scientific domains, data is coded in large tables or higher-dimensional arrays. Compressing these data into smaller, more manageable representations is...
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