1 citations · 2 across the 2 of their papers we have counts for
4 papers
Quasi-optimal -finite element refinements towards singularities via deep neural network prediction
Tomasz Sluzalec, Rafal Grzeszczuk, Sergio Rojas +2
We show how to construct the deep neural network (DNN) expert to predict quasi-optimal -refinements for a given computational problem. The main idea is to train the DNN expert…
SuperNet -- An efficient method of neural networks ensembling
Ludwik Bukowski, Witold Dzwinel
The main flaw of neural network ensembling is that it is exceptionally demanding computationally, especially, if the individual sub-models are large neural networks, which must be…
Supermodeling of tumor dynamics with parallel isogeometric analysis solver
Maciej Paszynski, Leszek Siwik, Witold Dzwinel +1
Supermodeling is a modern, model-ensembling paradigm that integrates several self-synchronized imperfect sub-models by controlling a few meta-parameters to generate more accurate p…
2-D Embedding of Large and High-dimensional Data with Minimal Memory and Computational Time Requirements
Witold Dzwinel, Rafal Wcislo, Stan Matwin
In the advent of big data era, interactive visualization of large data sets consisting of M*10^5+ high-dimensional feature vectors of length N (N ~ 10^3+), is an indispensable tool…