59 citations · 272 across the 21 of their papers we have counts for
22 papers
Toward an Effective Theory of Neurodynamics: Topological Supersymmetry Breaking, Network Coarse-Graining, and Instanton Interaction
Igor V. Ovchinnikov, Skirmantas Janusonis
Experimental research has shown that the brain's fast electrochemical dynamics, or neurodynamics (ND), is strongly stochastic, chaotic, and instanton (neuroavalanche)-dominated. It…
Dynamical field inference and supersymmetry
Margret Westerkamp, Igor Ovchinnikov, Philipp Frank +1
Knowledge on evolving physical fields is of paramount importance in science, technology, and economics. Dynamical field inference (DFI) addresses the problem of reconstructing a st…
Digital Memcomputing: from Logic to Dynamics to Topology
Massimiliano Di Ventra, Igor V. Ovchinnikov
Digital memcomputing machines (DMMs) are a class of computational machines designed to solve combinatorial optimization problems. A practical realization of DMMs can be accomplishe…
A neuronal dynamics study on a neuromorphic chip
Wenyuan Li, Igor V. Ovchinnikov, Honglin Chen +7
Neuronal firing activities have attracted a lot of attention since a large population of spatiotemporal patterns in the brain is the basis for adaptive behavior and can also reveal…
Chaos or Order?
Igor V. Ovchinnikov, Massimiliano Di Ventra
What is chaos? Despite several decades of research on this ubiquitous and fundamental phenomenon there is yet no agreed-upon answer to this question. Recently, it was realized that…
An Inexact Inverse Power Method for Numerical Analysis of Stochastic Dynamic Systems
Yuquan Sun, Fanghui Gong, Igor V. Ovchinnikov +1
This paper proposes an efficient method for computing partial eigenvalues of large sparse matrices what can be called the inexact inverse power method (IIPM). It is similar to the…