32 citations · 33 across the 5 of their papers we have counts for
3 papers · 1 filter
Extracting Global Dynamics of Loss Landscape in Deep Learning Models
Mohammed Eslami, Hamed Eramian, Marcio Gameiro +2
Deep learning models evolve through training to learn the manifold in which the data exists to satisfy an objective. It is well known that evolution leads to different final states…
Rational design of complex phenotype via network models
Marcio Gameiro, Tomas Gedeon, Shane Kepley +1
We demonstrate a modeling and computational framework that allows for rapid screening of thousands of potential network designs for particular dynamic behavior. To illustrate this…
A Framework for the Numerical Computation and a Posteriori Verification of Invariant Objects of Evolution Equations
Jordi-Lluís Figueras, Marcio Gameiro, Jean Philippe Lessard +1
We develop a theoretical framework for computer-assisted proofs of the existence of invariant objects in semilinear PDEs. The invariant objects considered in this paper are equilib…