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N. Lynch

17 papers hereh-index 6929k citations426 works total

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

author position
  • first author3
  • middle author5
  • last author9

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.DC10
  • cs.MA2
  • q-bio.NC2
  • cs.LG1
  • cs.NE1
  • cs.NI1
same name
  • N. Lynch — 1 paper, h 1
  • N. Lynch — 1 paper, h 8

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
20122021
most citedWinner-Take-All Computation in Spiking Neural Networks

10 citations · 18 across the 10 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.DC2019★ 1 cited

How to Color a French Flag--Biologically Inspired Algorithms for Scale-Invariant Patterning

Alberto Ancona, Ayesha Bajwa, Nancy Lynch +1

In the French flag problem, initially uncolored cells on a grid must differentiate to become blue, white or red. The goal is for the cells to color the grid as a French flag, i.e.,…

cs.DC2019★ 10 cited

Winner-Take-All Computation in Spiking Neural Networks

Nancy Lynch, Cameron Musco, Merav Parter

In this work we study biological neural networks from an algorithmic perspective, focusing on understanding tradeoffs between computation time and network complexity. Our goal is t…

q-bio.NC2019★ 1 cited

Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits

Lili Su, Chia-Jung Chang, Nancy Lynch

Winner-Take-All (WTA) refers to the neural operation that selects a (typically small) group of neurons from a large neuron pool. It is conjectured to underlie many of the brain's f…

cs.DC2019

Integrating Temporal Information to Spatial Information in a Neural Circuit

Nancy Lynch, Mien Brabeeba Wang

In this paper, we consider networks of deterministic spiking neurons, firing synchronously at discrete times; such spiking neural networks are inspired by networks of neurons and s…

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