@article{SysoevPonomarenkoPikovskij2017,
  author    = {Sysoev, Ilya V. and Ponomarenko, Vladimir I. and Pikovskij, Arkadij},
  title     = {Reconstruction of coupling architecture of neural field networks from vector time series},
  series = {Communications in nonlinear science \& numerical simulation},
  volume    = {57},
  journal   = {Communications in nonlinear science \& numerical simulation},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1007-5704},
  doi       = {10.1016/j.cnsns.2017.10.006},
  pages     = {342 -- 351},
  year      = {2017},
  abstract  = {We propose a method of reconstruction of the network coupling matrix for a basic voltage-model of the neural field dynamics. Assuming that the multivariate time series of observations from all nodes are available, we describe a technique to find coupling constants which is unbiased in the limit of long observations. Furthermore, the method is generalized for reconstruction of networks with time-delayed coupling, including the reconstruction of unknown time delays. The approach is compared with other recently proposed techniques.},
  language  = {en}
}
@article{GairingHoegeleKosenkova2017,
  author    = {Gairing, Jan and H{\"o}gele, Michael and Kosenkova, Tetiana},
  title     = {Transportation distances and noise sensitivity of multiplicative Levy SDE with applications},
  series = {Stochastic processes and their application},
  volume    = {128},
  journal   = {Stochastic processes and their application},
  number    = {7},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-4149},
  doi       = {10.1016/j.spa.2017.09.003},
  pages     = {2153 -- 2178},
  year      = {2017},
  abstract  = {This article assesses the distance between the laws of stochastic differential equations with multiplicative Levy noise on path space in terms of their characteristics. The notion of transportation distance on the set of Levy kernels introduced by Kosenkova and Kulik yields a natural and statistically tractable upper bound on the noise sensitivity. This extends recent results for the additive case in terms of coupling distances to the multiplicative case. The strength of this notion is shown in a statistical implementation for simulations and the example of a benchmark time series in paleoclimate.},
  language  = {en}
}