Embedded thumbnail for Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs [video]
Recorded:
Oct 25, 2019
Uploaded:
February 10, 2020
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
Martin Schrimpf
Speaker(s):
Jonas Kubilius
Lead authors Jonas Kubilius and Martin Schrimpf discuss the challenges of measuring how closely neural networks match the brain and present a new scoring method Brain-Score they have developed to evaluate models of the brain’s ventral stream at...
Embedded thumbnail for Doing for robots what nature did for us
Recorded:
Feb 4, 2020
Uploaded:
February 5, 2020
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
CBMM Speaker(s):
Leslie P. Kaelbling
Abstract: We, as robot engineers, have to think hard about our role in the design of robots and how it interacts with learning, both in "the factory" (that is, at engineering time) and in "the wild" (that is, when the robot is delivered to a...
Embedded thumbnail for Finding Friend and Foe in Multi-Agent Games [video]
Recorded:
Dec 16, 2019
Uploaded:
December 20, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
Max Kleiman-Weiner
Speaker(s):
Jack Serrino
Co-authors Max Kleiman-Weiner and Jack Serrino discuss their latest publication where they created a new algorithm. The algorithm that the team developed, dubbed DeepRole, has three components. First, it plays against itself, iteratively, with...
Embedded thumbnail for Metamers of neural networks reveal divergence from human perceptual systems [video]
Recorded:
Nov 25, 2019
Uploaded:
December 4, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
Jenelle Feather, Josh McDermott
First author and MIT graduate student Jenelle Feather and MIT Associate Professor Josh McDermott discuss their recent paper, part of the NIPS 2019 Proceedings, where they investigated whether the invariances learned by deep neural networks actually...
Embedded thumbnail for Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy
Recorded:
Oct 29, 2019
Uploaded:
November 27, 2019
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Thomas Icard
Thomas Icard, Stanford Abstract: How might we assess the expressive capacity of different classes of probabilistic generative models? The subject of this talk is an approach that appeals to machines of increasing strength (finite-state, recursive,...
Embedded thumbnail for A conversation with Prof. Thomas Serre
Recorded:
Nov 5, 2019
Uploaded:
November 7, 2019
Part of
All Captioned Videos, Scientific Interviews
CBMM Speaker(s):
Kamila Jozwik
Speaker(s):
Thomas Serre
On November 5, 2019, CBMM Postdoctoral Fellow Kamila Jóźwik took the opportunity to sit down and chat briefly with Prof. Thomas Serre of Brown University.
Embedded thumbnail for Feedforward and feedback processes in visual recognition
Recorded:
Nov 5, 2019
Uploaded:
November 6, 2019
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Thomas Serre
Thomas Serre - Cognitive, Linguistic & Psychological Sciences Department, Carney Institute for Brain Science, Brown University Abstract: Progress in deep learning has spawned great successes in many engineering applications. As a prime example,...
Embedded thumbnail for Beyond Empirical Risk Minimization: the lessons of deep learning
Recorded:
Oct 28, 2019
Uploaded:
October 29, 2019
Part of
All Captioned Videos, CBMM Special Seminars
Speaker(s):
Mikhail Belkin
Mikhail Belkin, Professor, The Ohio State University - Department of Computer Science and Engineering, Department of Statistics, Center for Cognitive Science Abstract: "A model with zero training error is  overfit to the training data and  will...
Embedded thumbnail for Joshua Tenenbaum, Cognitive Scientist | 2019 MacArthur Fellow
Recorded:
Sep 25, 2019
Uploaded:
September 25, 2019
Part of
All Captioned Videos, CBMM Research
CBMM Speaker(s):
Joshua Tenenbaum
Joshua Tenenbaum is a cognitive scientist. He is combining computational models with behavioral experiments to shed light on human learning, reasoning, and perception, and exploring how to bring artificial intelligence closer to the capabilities of...
Embedded thumbnail for Neuroscience Methods Tutorial (44:08)
Recorded:
Aug 11, 2019
Uploaded:
September 20, 2019
Part of
All Captioned Videos, Brains, Minds and Machines Summer Course 2019
CBMM Speaker(s):
Diego Mendoza-Halliday
Diego Mendoza-Halliday, MIT
Introduction to methods for recording, analyzing, and visualizing neural signals, focused on electrophysiology methods for acquiring signals that the brain uses to transmit information. This tutorial describes the...

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