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Liquid Neural Networks

Recorded:

Oct 5, 2021

Uploaded:

October 8, 2021

Part of

All Captioned Videos, CBMM Special Seminars

Speaker(s):

Ramin Hasani, Daniela Rus

Ramin Hasani, MIT - intro by Daniela Rus, MIT Abstract: In this talk, we will discuss the nuts and bolts of the novel continuous-time neural network models: Liquid Time-Constant (LTC) Networks. Instead of declaring a learning system's dynamics by...

Embedded thumbnail for Parallel systems for social and spatial reasoning within the brain&#039;s apex network

Parallel systems for social and spatial reasoning within the brain's apex network

Recorded:

Apr 27, 2021

Uploaded:

October 5, 2021

Part of

All Captioned Videos, CBMM Research

CBMM Speaker(s):

Ben Deen

What is the cognitive and neural architecture of core reasoning systems for understanding people and places? In this talk, we will outline a novel theoretical framework, arguing that internal models of people and places are implemented by two...

Towards a mechanistic understanding of compositionality

Recorded:

Sep 28, 2021

Uploaded:

September 30, 2021

Part of

All Captioned Videos, CBMM Research

CBMM Speaker(s):

Lucas Tian

Efficient representation, learning, and planning through abstraction: clustering cognitive spaces into submaps

Recorded:

Sep 15, 2021

Uploaded:

September 15, 2021

Part of

All Captioned Videos, Brains, Minds and Machines Seminar Series

CBMM Speaker(s):

Ila Fiete

Abstract: Episodic memory involves fragmenting the continuous stream of experience into discrete episodes. Not coincidentally, the hippocampus, which plays a central role in both episodic memory and spatial navigation, represents large spatial...

Tutorial: Recurrent neural networks for cognitive neuroscience

Recorded:

Aug 30, 2021

Uploaded:

August 30, 2021

Part of

Computational Tutorials

CBMM Speaker(s):

Guangyu Robert Yang

Robert Guangyu Yang, MIT In this hands-on tutorial, we will work together through a number of coding exercises to see how RNNs can be easily used to study cognitive neuroscience questions. We will train and analyze RNNs on various cognitive...