24 citations · 122 across the 27 of their papers we have counts for
36 papers
Robustness Against Outliers For Deep Neural Networks By Gradient Conjugate Priors
Pavel Gurevich, Hannes Stuke
We analyze a new robust method for the reconstruction of probability distributions of observed data in the presence of output outliers. It is based on a so-called gradient conjugat…
Asymptotics of the heat kernels on 2D lattices
Pavel Gurevich
We obtain asymptotic expansions of the spatially discrete 2D heat kernels, or Green's functions on lattices, with respect to powers of time variable up to an arbitrary order and es…
Gradient conjugate priors and multi-layer neural networks
Pavel Gurevich, Hannes Stuke
The paper deals with learning probability distributions of observed data by artificial neural networks. We suggest a so-called gradient conjugate prior (GCP) update appropriate for…
Stability of Periodic Solutions for Hysteresis-Delay Differential Equations
Pavel Gurevich, Eyal Ron
We study an interplay between delay and discontinuous hysteresis in dynamical systems. After having established existence and uniqueness of solutions, we focus on the analysis of s…
Pulses in FitzHugh--Nagumo systems with rapidly oscillating coefficients
Pavel Gurevich, Sina Reichelt
This paper is devoted to pulse solutions in FitzHugh--Nagumo systems that are coupled parabolic equations with rapidly periodically oscillating coefficients. In the limit of vanish…
Pairing an arbitrary regressor with an artificial neural network estimating aleatoric uncertainty
Pavel Gurevich, Hannes Stuke
We suggest a general approach to quantification of different forms of aleatoric uncertainty in regression tasks performed by artificial neural networks. It is based on the simultan…