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MIT 6.S191 (2020): Machine Learning for Scent
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MIT Introduction to Deep Learning 6.S191: Lecture 10
Machine Learning for Scent
Lecturer: Alex Wiltschko (Google Brain)
January 2020
Lecture Outline
0:00 - Introduction
2:55 - Digitizing smell
4:28 - The sense of smell
10:11 - Problem setup
12:58 - Molecule fragrance dataset
16:00 - Baseline algorithms
18:14 - Graph neural networks
21:25 - Molecules to graphs
23:03 - Predicting odor descriptors
25:19 - The odor embedding space
27:58 - Molecular neighbors
30:04 - Generalization
32:34 - Explaining/interpreting predictions
36:49 - Summary and future work
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Machine Learning for Scent
Lecturer: Alex Wiltschko (Google Brain)
January 2020
Lecture Outline
0:00 - Introduction
2:55 - Digitizing smell
4:28 - The sense of smell
10:11 - Problem setup
12:58 - Molecule fragrance dataset
16:00 - Baseline algorithms
18:14 - Graph neural networks
21:25 - Molecules to graphs
23:03 - Predicting odor descriptors
25:19 - The odor embedding space
27:58 - Molecular neighbors
30:04 - Generalization
32:34 - Explaining/interpreting predictions
36:49 - Summary and future work
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!
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