A Constructive Mean-Field Analysis of Multi-Population Neural Networks with Random Synaptic Weights and Stochastic Inputs

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Protein 3D Structure Computed from Evolutionary Sequence Variation (2011, background): “A partial analogy can be drawn to the inverse Ising or Potts problem, in which heterogeneous local couplings between discrete state variables are derived from measurements of twopoint correlation functions [34,35,36,37,38].”
Direct-coupling analysis of residue coevolution captures native contacts across many protein families (2011, background): “For an overview over the relative performance of these algorithms on artificial data see [11].”
Spin glass models for a network of real neurons (2009, methodology): “Since making the ﬁrst version of our results available [13], this work has stimulated research into the tractability and approximate methods for solving the maximum entropy problem [14, 15, 16, 17, 18, 19] and generalizations of the pairwise model [20, 21, 22, 23].”
3D Protein Structure Predicted from Sequence (2011, unknown): “A partial analogy can be drawn to the inverse Ising or Potts problem, in which heterogeneous local couplings between discrete state variables are derived from measurements of two-‐point correlation func”
Spatiotemporal dynamics of continuum neural fields (2012, background): “The analysis can also be generalized to the case of quenched disorder in the weights between individual neurons [72, 218].”