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D. Taylor

48 papers hereh-index 222k citations72 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author13
  • middle author21
  • last author13

Across the 48 of 48 papers where every author was matched, so the position is known.

fields
  • nlin.AO15
  • physics.soc-ph14
  • cs.SI6
  • cs.LG3
  • cond-mat.dis-nn2
  • cond-mat.soft1
same name
  • D. Taylor — 27 papers, h 20
  • D. Taylor — 20 papers, h 32
  • D. Taylor — 14 papers
  • D. Taylor — 14 papers
  • D. Taylor — 9 papers
  • D. Taylor — 8 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092026
most citedCausal Network Inference by Optimal Causation Entropy

222 citations · 1.3k across the 45 of their papers we have counts for

collaborators
Showing 2014Show all

4 papers · 1 filter

nlin.AO2014★ 62 cited

Erosion of synchronization in networks of coupled oscillators

Per Sebastian Skardal, Dane Taylor, Jie Sun +1

We report erosion of synchronization in networks of coupled phase oscillators, a phenomenon where perfect phase synchronization is unattainable in steady-state, even in the limit o…

nlin.AO2014★ 155 cited

Topological data analysis of contagion maps for examining spreading processes on networks

Dane Taylor, Florian Klimm, Heather A. Harrington +4

Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however,…

nlin.AO2014★ 160 cited

Optimal synchronization of complex networks

Per Sebastian Skardal, Dane Taylor, Jie Sun

We study optimal synchronization in networks of heterogeneous phase oscillators. Our main result is the derivation of a synchrony alignment function that encodes the interplay betw…

cs.IT2014★ 222 cited

Causal Network Inference by Optimal Causation Entropy

Jie Sun, Dane Taylor, Erik M. Bollt

The broad abundance of time series data, which is in sharp contrast to limited knowledge of the underlying network dynamic processes that produce such observations, calls for a rig…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.