Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
David Gow
David Gow, Massachusetts General Hospital
slides (PPTX) and associated video file (MOV)
Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
Dimitrios Pantazis
Dimitrios Pantazis, MIT - McGovern Institute for Brain Research
slides (PDF)
Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
Matti Hämäläinen
Matti Hämäläinen, Massachusetts General Hospital
slides (PDF)
Recorded:
May 2, 2019
Uploaded:
May 2, 2019
Part of
Scientific Interviews
CBMM Speaker(s):
Martin Schrimpf
Speaker(s):
Blake Richards
On April 26, 2019, CBMM graduate student Martin Schrimpf took the opportunity to sit down and chat briefly with Prof. Blake Richards of the University of Toronto / McGill University.
Recorded:
Apr 25, 2019
Uploaded:
May 2, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
James DiCarlo, Pouya Bashivan, Kohitij Kar
Center for Brains, Minds and Machines researchers and paper authors Jim DiCarlo, Pouya Bashivan and Kohitij Kar discuss their recent research findings as published in the journal Science.
Recorded:
Apr 25, 2019
Uploaded:
April 29, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
James DiCarlo, Kohitij Kar
Speaker(s):
Diane Beck
Center for Brains, Minds and Machines researchers and paper authors Jim DiCarlo and Kohitij Kar discuss their recent research findings as published in the journal Nature Neuroscience. Diane Beck of the University of Illinois, Beckman Institute...
Recorded:
Apr 26, 2019
Uploaded:
April 26, 2019
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Blake Richards
Blake Richards, Assistant Professor, Associate Fellow of the Canadian Institute for Advanced Research (CIFAR)
Abstract:
Theoretical and empirical results in the neural networks literature demonstrate that effective learning at a real-world scale...
Recorded:
Apr 11, 2019
Uploaded:
April 19, 2019
Part of
Computational Tutorials
CBMM Speaker(s):
Kelsey Allen
Kelsey Allen, MIT
Common intuition posits that deep learning has succeeded because of its ability to assume very little structure in the data it receives, instead learning that structure from large numbers of training examples. However, recent work...
Recorded:
Apr 5, 2019
Uploaded:
April 8, 2019
Part of
Scientific Interviews
CBMM Speaker(s):
Andrzej Banburski
Speaker(s):
Jon Bloom, Broad Institute
On April 5, 2019, CBMM Postdoc Andrzej Banburski took the opportunity to sit down and chat briefly with Dr. Jon Bloom of the Broad Institute.
Recorded:
Apr 2, 2019
Uploaded:
April 3, 2019
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Jon Bloom
Speaker: Dr. Jon Bloom, Broad Institute
Abstract: When trained to minimize reconstruction error, a linear autoencoder (LAE) learns the subspace spanned by the top principal directions but cannot learn the principal directions themselves. In...