3 papers
cs.LG2022
Learning via nonlinear conjugate gradients and depth-varying neural ODEs
George Baravdish, Gabriel Eilertsen, Rym Jaroudi +3
The inverse problem of supervised reconstruction of depth-variable (time-dependent) parameters in a neural ordinary differential equation (NODE) is considered, that means finding t…
math.OC2019
Iterative TV minimization on the graph
Japhet Niyobuhungiro, Eric Setterqvist, Freddie Åström +1
We define the space of functions of bounded variation () on the graph. Using the notion of divergence of flows on graphs, we show that the unit ball of the dual space to i…
math.NA2018
Damped second order flow applied to image denoising
George Baravdish, Olof Svensson, Mårten Gulliksson +1
In this paper, we introduce a new image denoising model: the damped flow (DF), which is a second order nonlinear evolution equation associated with a class of energy functionals of…