90 citations · 91 across the 5 of their papers we have counts for
5 papers
Deep Learning for Model Calibration in Simulation of Itaconic Acid Production
Daria Fokina, Marco Baldan, Constantin Romankiewicz +3
In this study, deep learning is used to estimate kinetic parameters for modeling itaconic acid production based on real batch experiments conducted at different agitation speeds an…
Machine learning methods for prediction of breakthrough curves in reactive porous media
Daria Fokina, Pavel Toktaliev, Oleg Iliev +1
Reactive flows in porous media play an important role in our life and are crucial for many industrial, environmental and biomedical applications. Very often the concentration of th…
On the Performance of Machine Learning Methods for Breakthrough Curve Prediction
Daria Fokina, Oleg Iliev, Pavel Toktaliev +2
Reactive flows are important part of numerous technical and environmental processes. Often monitoring the flow and species concentrations within the domain is not possible or is ex…
Growing axons: greedy learning of neural networks with application to function approximation
Daria Fokina, Ivan Oseledets
We propose a new method for learning deep neural network models that is based on a greedy learning approach: we add one basis function at a time, and a new basis function is genera…
Microstructure synthesis using style-based generative adversarial network
Daria Fokina, Ekaterina Muravleva, George Ovchinnikov +1
Work considers the usage of StyleGAN architecture for the task of microstructure synthesis. The task is the following: given number of samples of structure we try to generate simil…