Tomasz Sluzalec

According to our database, Tomasz Sluzalec authored at least 11 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Stabilization of isogeometric finite element method with optimal test functions computed from L2 norm residual minimization.

Marcin Los, Tomasz Sluzalec, Maciej Paszynski, Eirik Valseth

J. Comput. Appl. Math., 2025

Tensorial Implementation for Robust Variational Physics-Informed Neural Networks.

Askold Vilkha, Carlos Uriarte, Pawel Maczuga, Tomasz Sluzalec, Maciej Paszynski

Proceedings of the Computational Science - ICCS 2025, 2025

Augmenting Petrov-Galerkin Method with Optimal Test Functions by DNN Learning the Inverse of the Gram Matrix.

Tomasz Sluzalec

Proceedings of the Computational Science - ICCS 2025 Workshops, 2025

Physics Informed Neural Network Code for 2D Transient Problems (PINN-2DT) Compatible with Google Colab.

Pawel Maczuga, Maciej Sikora, Tomasz Sluzalec, Marcin Szubert, Lukasz Sztangret, Danuta Szeliga, Marcin Los, Witold Dzwinel, Keshav Pingali, Maciej Paszynski

Proceedings of the Computational Science - ICCS 2025, 2025

Physics Informed Neural Networks for Non-stationary Material Science Problems.

Pawel Maczuga, Tomasz Sluzalec, Lukasz Sztangret, Danuta Szeliga, Marcin Los, Maciej Paszynski

Proceedings of the Computational Science - ICCS 2025 Workshops, 2025

2024

Stabilization of isogeometric finite element method with optimal test functions computed from L₂ norm residual minimization.

Marcin Los, Tomasz Sluzalec, Maciej Paszynski, Eirik Valseth

CoRR, 2024

2023

Quasi-optimal <i>hp</i>-finite element refinements towards singularities via deep neural network prediction.

Tomasz Sluzalec, Rafal Wojciech Grzeszczuk, Sergio Rojas, Witold Dzwinel, Maciej Paszynski

Comput. Math. Appl., 2023

Fast Solver for Advection Dominated Diffusion Using Residual Minimization and Neural Networks.

Tomasz Sluzalec, Maciej Paszynski

Proceedings of the Computational Science - ICCS 2023, 2023

2022

Automatic stabilization of finite-element simulations using neural networks and hierarchical matrices.

Tomasz Sluzalec, Mateusz Dobija, Anna Paszynska, Ignacio Muga, Maciej Paszynski

CoRR, 2022

Quasi-optimal hp-finite element refinements towards singularities via deep neural network prediction.

Tomasz Sluzalec, Rafal Wojciech Grzeszczuk, Sergio Rojas, Witold Dzwinel, Maciej Paszynski

CoRR, 2022

2020

Securing Data of Biotechnological Laboratories Using Blockchain Technology.

Krzysztof Misztal, Tomasz Sluzalec, Aleksandra Kubica-Misztal

Proceedings of the Computer Information Systems and Industrial Management, 2020