Recorded:
Apr 28, 2020
Uploaded:
May 5, 2020
Part of
All Captioned Videos, CBMM Research
Speaker(s):
Youssef Mroueh, IBM Research and MIT-IBM Watson AI lab
Youssef Mroueh, IBM Research and MIT-IBM Watson AI lab
Abstract: In this talk I will show how learning gradients help us designing new non-linear algorithms for feature selection, black box sampling and also, in understanding neural style transfer....
Recorded:
Apr 21, 2020
Uploaded:
April 23, 2020
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Luca Carlone, MIT
Abstract:
Spatial perception has witnessed an unprecedented progress in the last decade. Robots are now able to detect objects and create large-scale maps of an unknown environment, which are crucial capabilities for navigation and...
Spatial perception has witnessed an unprecedented progress in the last decade. Robots are now able to detect objects and create large-scale maps of an unknown environment, which are crucial capabilities for navigation and...
Recorded:
Apr 15, 2020
Uploaded:
April 15, 2020
Part of
All Captioned Videos, CBMM Research
CBMM Speaker(s):
Tomaso Poggio, Lorenzo Rosasco
Speaker(s):
Mikhail Belkin, Constantinos Daskalakis, Gil Strang
A panel discussion featuring Tomaso Poggio (CBMM), Mikhail Belkin (Ohio State University), Constantinos Daskalakis (CSAIL), Gil Strang (Mathematics) and Lorenzo Rosasco (University of Genova).
Abstract: Developing theoretical foundations for...
Recorded:
Apr 7, 2020
Uploaded:
April 7, 2020
Part of
All Captioned Videos, CBMM Research
CBMM Speaker(s):
Samuel Gershman
Sam Gershman, Harvard University
Abstract: In this talk, I will present a theory of reinforcement learning that falls in between "model-based" and "model-free" approaches. The key idea is to represent a "predictive map" of the environment, which can...
Recorded:
Apr 1, 2020
Uploaded:
April 1, 2020
Part of
All Captioned Videos, CBMM Special Seminars
CBMM Speaker(s):
Amnon Shashua
Speaker(s):
Shai Shalev-Shwartz
Abstract:
We present an analysis of a risk-based selective quarantine model where the population is divided into low and high-risk groups. The high-risk group is quarantined until the low-risk group achieves herd-immunity. We tackle the...
We present an analysis of a risk-based selective quarantine model where the population is divided into low and high-risk groups. The high-risk group is quarantined until the low-risk group achieves herd-immunity. We tackle the...
Recorded:
Feb 25, 2020
Uploaded:
March 9, 2020
Part of
Scientific Interviews
CBMM Speaker(s):
Andrzej Banburski
Speaker(s):
Michael R. Douglas, Simons Center for Geometry and Physics at Stony Brook University
On February 25, 2020, CBMM Postdoctoral Fellow Andrzej Banburski took the opportunity to sit down and chat briefly with Michael R. Douglas of the Simons Center for Geometry and Physics at Stony Brook University.
Recorded:
Jul 9, 2019
Uploaded:
March 9, 2020
Part of
All Captioned Videos, CBMM Special Seminars
Speaker(s):
Andrew Seeds - Institute for Neurobiology, University of Puerto Rico, Medical Sciences Campus
Recorded:
Feb 25, 2020
Uploaded:
February 26, 2020
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Michael R. Douglas, Stony Brook University
Recorded:
May 21, 2018
Uploaded:
February 26, 2020
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Jonathan Miller, OIST
![Embedded thumbnail for Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs [video]](https://cbmm.mit.edu/sites/default/files/styles/youtube_thumbnail_220w/public/youtube/IqkOZhfGEYs.jpg?itok=42RJOJiM)
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...