NS-CUK Seminar:H.E.Lee, Review on "Gated Graph Sequence Neural Net...

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Hyo Eun Lee
Network Science Lab
Dept. of Biotechnology
The Catholic University of Korea
E-mail: gydnsml@gmail.com
2023.07....

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 Explanation Application
• bAbI task
• Experiments
 Program Verification with GGS-NNS
 Related Work
 Discussion

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1. Explanation Application
bAbI task

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1. Explanation Application
bAbI task
• This method takes into account the time order of the data
, which provides additi...

4
1. Explanation Application
bAbI task
• Symbolic data is a type of data that previous studies have not been able to learn...

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1. Explanation Application
bAbI task
• Use tasks 4, 15, 16, and 18
• Two argumentation, basic inference, basic induction...

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1. Explanation Application
Experiments
• Use 50 out of 1000 examples as validation
• Training data is split between 100 ...

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1. Explanation Application
Experiments
• GGNN: Training with only 50
• LSTM and RNN performed poorly in all but Task 4

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1. Explanation Application
Experiments
• See how the number of training examples affects performance
• Both RNN and LSTM...

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1. Explanation Application
Experiments
• Existing studies, RNN and LSTM
, both fail to exceed 20 accuracy on task 19
• T...

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1. Explanation Application
Experiments
• Solving problems with algorithmic learning methods
• Shortest Paths: How to fi...

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2. Program Verification with GGS-NNS
Limitation of previous study
• Inferring program invariants to approximate
the set...

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3. Related Work
Convolution
• Emphasize that it extends traditional graph neural networks to sequences of outputs
• Thi...

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4. Discussion
Discussion
• Describes techniques for learning features from graph-structured inputs, focusing on GNNs an...

NS-CUK Seminar:H.E.Lee, Review on "Gated Graph Sequence Neural Networks", ICLR 2016

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