Granger causality using Jacobian in neural networks
Granger causality is a commonly used method for uncovering information flow and dependencies in a time series. Here, we introduce JGC (Jacobian Granger causality), a neural network-based approach to Granger causality using the Jacobian as a measure of variable importance, and propose a variable sele...
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Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/165593 |
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Institution: | Nanyang Technological University |
Language: | English |
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