Embedded thumbnail for THINGS: A large-scale global initiative to study the cognitive, computational, and neural mechanisms of object recognition in biological and artificial intelligence
Recorded:
Dec 12, 2020
Uploaded:
December 16, 2020
Part of
All Captioned Videos, SVRHM Workshop 2020
Speaker(s):
Martin Hebart
Martin Hebart, Max Planck Institute for Human Cognitive and Brain Sciences
Embedded thumbnail for SVRHM 2020 Opening Remarks
Recorded:
Dec 12, 2020
Uploaded:
December 16, 2020
Part of
All Captioned Videos, SVRHM Workshop 2020
CBMM Speaker(s):
Arturo Deza
Embedded thumbnail for How did you learn the natural numbers?
Recorded:
Aug 13, 2020
Uploaded:
December 10, 2020
Part of
All Captioned Videos, Brains, Minds and Machines Summer Course 2020
CBMM Speaker(s):
Pietro Perona
Pietro Perona, California Institute of Technology Link to manuscript - https://arxiv.org/abs/2012.04132
Embedded thumbnail for CBMM Panel Discussion: Should models of cortex be falsifiable?
Recorded:
Dec 1, 2020
Uploaded:
December 7, 2020
Part of
All Captioned Videos, CBMM Special Seminars
CBMM Speaker(s):
Tomaso Poggio, Gabriel Kreiman, Josh McDermott, Leyla Isik, Martin Schrimpf, Susan Epstein, Jenelle Feather
Speaker(s):
Thomas Serre, Michael Lee
Presenters: Prof. Tomaso Poggio (MIT), Prof. Gabriel Kreiman (Harvard Medical School, BCH), and Prof. Thomas Serre (Brown U.)
Discussants: Prof. Leyla Isik (JHU), Martin Schrimpf (MIT), Michael Lee (MIT), Prof. Susan Epstein (Hunter CUNY), and...
Embedded thumbnail for Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations [video]
Recorded:
Dec 3, 2020
Uploaded:
December 3, 2020
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
Tiago Marques, James DiCarlo
Speaker(s):
Joel Dapello
Hear from the lead authors Tiago Maques (MIT), Joel Dapello (Harvard), and PI James DiCarlo (MIT), about their development of VOneNets, a new class of hybrid CNN vision models. This paper was accepted in the Advances in Neural Information Processing...
Embedded thumbnail for Why Do Our Models Learn?
Recorded:
Nov 24, 2020
Uploaded:
November 25, 2020
Part of
All Captioned Videos, CBMM Research
Speaker(s):
Aleksander Madry, MIT
Abstract:  Large-scale vision benchmarks have driven---and often even defined---progress in machine learning. However, these benchmarks are merely proxies for the real-world tasks we actually care about. How well do our benchmarks capture such tasks...
Embedded thumbnail for Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning [video]
Recorded:
Nov 23, 2020
Uploaded:
November 23, 2020
Part of
All Captioned Videos, Publication Releases, CBMM Research
CBMM Speaker(s):
Kevin Smith, Kelsey Allen, Joshua Tenenbaum
Authors Kelsey Allen, Kevin Smith, and Joshua Tenenbaum describe their newly published paper in PNAS about a new cognitive model that learns to use tools like humans do.
Embedded thumbnail for Linear Analysis of RNN Dynamics
Recorded:
Nov 19, 2020
Uploaded:
November 23, 2020
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Eli Pollock
Recurrent neural networks (RNNs) are a powerful model for neural and cognitive phenomena. However, interpreting these models can be a challenge. In this tutorial, we will discuss how dynamical systems theory provides some tools for understanding...
Embedded thumbnail for Children Helping Science!
Recorded:
Nov 6, 2020
Uploaded:
November 6, 2020
Part of
All Captioned Videos, CBMM Research
ChildrenHelpingScience.com is a website where you and your family can find and participate in online research studies from universities around the world! You can search for the perfect study for your family. We have studies for all ages, starting...
Embedded thumbnail for Representations vs Algorithms: Symbols and Geometry in Robotics
Recorded:
Nov 3, 2020
Uploaded:
November 4, 2020
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
CBMM Speaker(s):
Nicholas Roy
In the last few years, the ability for robots to understand and operate in the world around them has advanced considerably. Examples include the growing number of self-driving car systems, the considerable work in robot mapping, and the growing...

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