Recurrent Neural Networks RNNs, Graph Neural Networks GNNs, Long Short Term Memory LSTMs
Manolis Kellis Manolis Kellis
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 Published On Mar 2, 2021

Deep Learning in Life Sciences - Lecture 04 - RNNs, LSTMs, Transformers, GNNs (Spring 2021)
6.874/6.802/20.390/20.490/HST.506 Spring 2021 Prof. Manolis Kellis
Deep Learning in the Life Sciences / Computational Systems Biology
Playlist:    • MIT Deep Learning in Life Sciences - ...  
Latest slides and course today: http://compbio.mit.edu/6874
Spring 2021 slides and materials: http://mit6874.github.io/

0:00 Introduction, agenda
2:15 Context demonstration
9:05 Sequential models
13:35 Hidden Markov Models
19:50 Recurrent neural networks
25:10 RNN architectures
33:30 Backpropagation through time
36:12 Increasing memory length
39:35 Long short term memory
45:35 Application: reading cursive
49:15 Training an RNN
51:32 Transformers
56:40 Graph neural networks (guest lecture)
1:02:05 Applications of GNNs
1:03:20 Problem setup
1:06:44 How a GNN works
1:19:43 GNN variants
1:27:45 GNN applications
1:31:45 Conclusion

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