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Alex Tank, Ian Covert, Nicholas J. Foti, Ali Shojaie, Emily B. Fox
While most classical approaches to Granger causality detection assume linear dynamics, many interactions in real-world applications, like neuroscience and genomics, are inherently nonlinear. In these cases, using linear models may lead to inconsistent estimation of Granger causal interactions. We propose a class of nonlinear methods by applying structured multilayer perceptrons (MLPs) or recurrent neural networks (RNNs) combined with sparsity-inducing penalties on the weights. By encouraging specific sets of weights to be zero-in particular, through the use of convex group-lasso penalties-we can extract the Granger causal structure. To further contrast with traditional approaches, our framework naturally enables us to efficiently capture long-range dependencies between series either via our RNNs or through an automatic lag selection in the MLP. We show that our neural Granger causality methods outperform state-of-the-art nonlinear Granger causality methods on the DREAM3 challenge data. This data consists of nonlinear gene expression and regulation time courses with only a limited number of time points. The successes we show in this challenging dataset provide a powerful example of how deep learning can be useful in cases that go beyond prediction on large datasets. We likewise illustrate our methods in detecting nonlinear interactions in a human motion capture dataset.
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Tank, A., Covert, I., Foti, N. J., Shojaie, A., & Fox, E. B. (2021). Neural Granger Causality. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(8), 1. https://doi.org/10.1109/tpami.2021.3065601
Tank, Alex, et al. "Neural Granger Causality." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 8, 2021, pp. 1, https://doi.org/10.1109/tpami.2021.3065601.
Tank, Alex, Ian Covert, Nicholas J. Foti, Ali Shojaie, and Emily B. Fox. "Neural Granger Causality." IEEE Transactions on Pattern Analysis and Machine Intelligence 44, no. 8 (2021): 1. https://doi.org/10.1109/tpami.2021.3065601.
Tank A., Covert I., Foti N. J. [и др.] Neural Granger Causality // IEEE Transactions on Pattern Analysis and Machine Intelligence. — 2021. — Vol. 44, № 8. — P. 1. — URL: https://doi.org/10.1109/tpami.2021.3065601
@article{tank2021neural,
title = {{Neural Granger Causality}},
author = {Alex Tank and Ian Covert and Nicholas J. Foti and Ali Shojaie and Emily B. Fox},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2021},
volume = {44},
number = {8},
pages = {1},
doi = {10.1109/tpami.2021.3065601},
url = {https://doi.org/10.1109/tpami.2021.3065601}
}TY - JOUR AU - Tank, Alex AU - Covert, Ian AU - Foti, Nicholas J. AU - Shojaie, Ali AU - Fox, Emily B. TI - Neural Granger Causality JO - IEEE Transactions on Pattern Analysis and Machine Intelligence VL - 44 IS - 8 SP - 1 PY - 2021 DA - 2021/01/01 DO - 10.1109/tpami.2021.3065601 UR - https://doi.org/10.1109/tpami.2021.3065601 ER -
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