Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems

Jimmy T. H. Smith, Scott W. Linderman, David Sussillo. Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 16700-16713, 2021. [doi]

@inproceedings{SmithLS21,
  title = {Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems},
  author = {Jimmy T. H. Smith and Scott W. Linderman and David Sussillo},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/8b77b4b5156dc11dec152c6c71481565-Abstract.html},
  researchr = {https://researchr.org/publication/SmithLS21},
  cites = {0},
  citedby = {0},
  pages = {16700-16713},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}