NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations

  title={NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations},
  author={Marco Ciccone and Marco Gallieri and Jonathan Masci and Christian Osendorfer and Faustino J. Gomez},
This paper introduces Non-Autonomous Input-Output Stable Network (NAIS-Net), a very deep architecture where each stacked processing block is derived from a time-invariant non-autonomous dynamical system. Non-autonomy is implemented by skip connections from the block input to each of the unrolled processing stages and allows stability to be enforced so that blocks can be unrolled adaptively to a pattern-dependent processing depth. NAIS-Net induces non-trivial, Lipschitz input-output maps, even… CONTINUE READING
Recent Discussions
This paper has been referenced on Twitter 6 times over the past 90 days. VIEW TWEETS


Publications citing this paper.
Showing 1-2 of 2 extracted citations


Publications referenced by this paper.
Showing 1-10 of 52 references

Stability analysis of recurrent neural networks with applications

  • J. N. Knight
  • Colorado State University,
  • 2008
Highly Influential
5 Excerpts

Untersuchungen zu dynamischen neuronalen netzen

  • S. Hochreiter
  • diploma thesis,
  • 1991
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…