86 citations · 96 across the 4 of their papers we have counts for
4 papers
Achieving Occam's Razor: Deep Learning for Optimal Model Reduction
Botond B Antal, Anthony G Chesebro, Helmut H Strey +2
All fields of science depend on mathematical models. Occam's razor refers to the principle that good models should exclude parameters beyond those minimally required to describe th…
The refractory period matters: unifying mechanisms of macroscopic brain waves
Corey Weistuch, Lilianne R. Mujica-Parodi, Ken Dill
The relationship between complex, brain oscillations and the dynamics of individual neurons is poorly understood. Here we utilize Maximum Caliber, a dynamical inference principle,…
Inferring a network from dynamical signals at its nodes
Corey Weistuch, Luca Agozzino, Lilianne R. Mujica-Parodi +1
We give an approximate solution to the difficult inverse problem of inferring the topology of an unknown network from given time-dependent signals at the nodes. For example, we mea…
Maximum Caliber: a general variational principle for dynamical systems
Purushottam D. Dixit, Jason Wagoner, Corey Weistuch +3
We review here {\it Maximum Caliber} (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical tr…