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Co-Authors

This is a "connection" page, showing publications co-authored by Daniel Margoliash and Henry Abarbanel.

 
Connection Strength
 
 
 
2.500
 
  1. Abarbanel HDI, Shirman S, Breen D, Kadakia N, Rey D, Armstrong E, Margoliash D. Response to "Comment on 'A unifying view of synchronization for data assimilation in complex nonlinear networks'" [Chaos 28, 028101 (2018)]. Chaos. 2018 02; 28(2):028102.
    View in: PubMed
    Score: 0.791
  2. Abarbanel HDI, Shirman S, Breen D, Kadakia N, Rey D, Armstrong E, Margoliash D. A unifying view of synchronization for data assimilation in complex nonlinear networks. Chaos. 2017 Dec; 27(12):126802.
    View in: PubMed
    Score: 0.782
  3. Kadakia N, Armstrong E, Breen D, Morone U, Daou A, Margoliash D, Abarbanel HD. Nonlinear statistical data assimilation for HVC[Formula: see text] neurons in the avian song system. Biol Cybern. 2016 12; 110(6):417-434.
    View in: PubMed
    Score: 0.180
  4. Nogaret A, Meliza CD, Margoliash D, Abarbanel HD. Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data. Sci Rep. 2016 09 08; 6:32749.
    View in: PubMed
    Score: 0.180
  5. Meliza CD, Kostuk M, Huang H, Nogaret A, Margoliash D, Abarbanel HD. Estimating parameters and predicting membrane voltages with conductance-based neuron models. Biol Cybern. 2014 Aug; 108(4):495-516.
    View in: PubMed
    Score: 0.154
  6. Knowlton C, Meliza CD, Margoliash D, Abarbanel HD. Dynamical estimation of neuron and network properties III: network analysis using neuron spike times. Biol Cybern. 2014 Jun; 108(3):261-73.
    View in: PubMed
    Score: 0.152
  7. Kostuk M, Toth BA, Meliza CD, Margoliash D, Abarbanel HD. Dynamical estimation of neuron and network properties II: Path integral Monte Carlo methods. Biol Cybern. 2012 Mar; 106(3):155-67.
    View in: PubMed
    Score: 0.132
  8. Toth BA, Kostuk M, Meliza CD, Margoliash D, Abarbanel HD. Dynamical estimation of neuron and network properties I: variational methods. Biol Cybern. 2011 Oct; 105(3-4):217-37.
    View in: PubMed
    Score: 0.128
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.