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- University of California San DiegoUS25 papers
- Center for Theoretical Biological PhysicsUS6 papers
- Tel Aviv UniversityIL6 papers
- Stanford UniversityUS5 papers
- Harvard UniversityUS4 papers
- Institut national de recherche en sciences et technologies du numériqueFR4 papers
- Northeastern UniversityUS4 papers
- Baylor College of MedicineUS3 papers
- Columbia UniversityUS3 papers
- Georgia Institute of TechnologyUS3 papers
- Imperial College LondonGB3 papers
- Lawrence Berkeley National LaboratoryUS3 papers
4 papers · 1 filter
Learning Moment Closure in Reaction-Diffusion Systems with Spatial Dynamic Boltzmann Distributions
Oliver K. Ernst, Tom Bartol, Terrence Sejnowski +1
Many physical systems are described by probability distributions that evolve in both time and space. Modeling these systems is often challenging to due large state space and analyt…
Learning Dynamic Boltzmann Distributions as Reduced Models of Spatial Chemical Kinetics
Oliver K. Ernst, Thomas Bartol, Terrence Sejnowski +1
Finding reduced models of spatially-distributed chemical reaction networks requires an estimation of which effective dynamics are relevant. We propose a machine learning approach t…
Time-resolved and time-scale adaptive measures of spike train synchrony
Thomas Kreuz, Daniel Chicharro, Martin Greschner +1
A wide variety of approaches to estimate the degree of synchrony between two or more spike trains have been proposed. One of the most recent methods is the ISI-distance which extra…
Maximally informative pairwise interactions in networks
Jeffrey D. Fitzgerald, Tatyana O. Sharpee
Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here…