In this video, we show how to apply the EM Algorithm to Magnetic Resonance Imaging for simultaneous bias field correction and image segmentation.
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This video explains a fundamental learning technique in reinforcement learning: Policy Iteration.
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Read the Transcript (Summer 2020) at:LMETowards Data Science
In this video, we analyze the expectation-maximization algorithm and relate it to Kullback-Leibler statistics in the context of the missing information principle.
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This video explains the basics of reinforcement learning: The Markov Decision Process and how to compute the expected future return.
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Read the Transcript (Summer 2020) at:LMETowards Data Science
This video explains the concepts of sequential decision making and the multi-armed bandit problem.
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Read the Transcript (Summer 2020) at:LMETowards Data Science
This video explains the concepts of attention in deep learning.
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Read the Transcript (Summer 2020) at:LMETowards Data Science
This is a video for everybody who is also interested in more philosophical topics such as conscious and self-aware machines. We did a small review of the state-of-the-art and present what we found.
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Read the Paper at:ArxivFrontiers on Computational Neuroscience
This video introduces gradient and optimization based visualization.
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Read the Transcript (Summer 2020) at:LMETowards Data Science
This video shows simple visualization techniques based on lesion studies and investigating activations.
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Read the Transcript (Summer 2020) at:LMETowards Data Science