CBMM Special Seminars
31 videos • 1,807 views • by MITCBMM
1
Solving Global Coordination by Jaan Tallinn
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2
Topological Treatment of Neural Activity and the Quantum Question Order Effect
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3
Demis Hassabis: Towards General Artificial Intelligence
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4
CBMM Research Meeting: On Compositionality (debate/discussion)
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5
On the Forgetting of College Academics and the Role of Learning Engineering in Building Expertise
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6
Spike Timing in Motor Control
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7
The Convergence of Machine Learning and Artificial Intelligence Towards Enabling Autonomous Driving
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8
EAC Panel on AI and Jobs
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9
Machine Learning Techniques and Applications in Finance, Healthcare and Recommendation Systems
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10
Noam Chomsky: Language and Evolution
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11
How Can the Brain Efficiently Build an Understanding of the Natural World
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12
Fit Without Fear: An Over-Fitting Perspective on Modern Deep and Shallow Learning
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13
Explore MIT Today: Reverse Engineering the Mind: Brain and Cognitive Sciences
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14
What are the differences between neural networks and the brain?
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15
Transformative Generative Models
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16
What information dynamics can tell us about ... brains
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17
Successes and challenges in modern artificial intelligence
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18
The Power of Self-Learning Systems
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19
Beyond Empirical Risk Minimization: the lessons of deep learning
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20
Exploring how the nervous system produces movement sequences
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21
Can we Contain Covid-19 without Locking-down the Economy?
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22
Improving Generalization by Self-Training & Self Distillation
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23
A Computational Explanation for Domain Specificity in the Human Visual System
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24
Panel Discussion on the relationship between engineering and science in CBMM and the field
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25
CBMM Panel Discussion: Is the theory of Deep Learning relevant to applications?
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26
CBMM Panel Discussion: Should models of cortex be falsifiable?
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27
From Associative Memories to Deep Networks and from Associative Memories to Universal Machines
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28
CBMM Panel Discussion: “Testing generative models in the brain”
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29
Banach Space Representer Theorems for Neural Networks
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30
Next-generation recurrent network models for cognitive neuroscience
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31
Liquid Neural Networks
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