Maximum likelihood estimation for constrained parameters of multinomial distributions - Application to Zipf-Mandelbrot models. - Ferenc Izsák (Comput. Stat. Data Anal., 2006)

Error Analysis of a Continuous-Discontinuous Galerkin Finite Element Method for Generalized 2D Vorticity Dynamics. - Jaap J. W. van der Vegt; Ferenc Izsák; Onno Bokhove (SIAM J. Numer. Anal., 2007)

Implicit a posteriori error estimates for the Maxwell equations. - Ferenc Izsák; Davit Harutyunyan; Jaap J. W. van der Vegt (Math. Comput., 2008)

Optimal Penalty Parameters for Symmetric Discontinuous Galerkin Discretisations of the Time-Harmonic Maxwell Equations. - D. Sármány; Ferenc Izsák; Jaap J. W. van der Vegt (J. Sci. Comput., 2010)

Energy norm error estimates for averaged discontinuous Galerkin methods: Multidimensional case. - Ferenc Izsák (Comput. Math. Appl., 2015)

Finite element approximation of fractional order elliptic boundary value problems. - Béla J. Szekeres; Ferenc Izsák (J. Comput. Appl. Math., 2016)

Models of space-fractional diffusion: A critical review. - Ferenc Izsák; Béla J. Szekeres (Appl. Math. Lett., 2017)

Finite difference approximation of space-fractional diffusion problems: The matrix transformation method. - Béla J. Szekeres; Ferenc Izsák (Comput. Math. Appl., 2017)

Hamiltonian Finite Element Discretization for Nonlinear Free Surface Water Waves. - Freekjan Brink; Ferenc Izsák; Jaap J. W. van der Vegt (J. Sci. Comput., 2017)

Efficient computation of matrix power-vector products: Application for space-fractional diffusion problems. - Ferenc Izsák; Béla J. Szekeres (Appl. Math. Lett., 2018)

Finite element methods for fractional-order diffusion problems with optimal convergence order. - Gábor Maros; Ferenc Izsák (Comput. Math. Appl., 2020)

Localization of Scattering Objects Using Neural Networks. - Domonkos Haffner; Ferenc Izsák (Sensors, 2021)

Neural-Network-Assisted Finite Difference Discretization for Numerical Solution of Partial Differential Equations. - Ferenc Izsák; Rudolf Izsák (Algorithms, 2023)

Learning Data for Neural-Network-Based Numerical Solution of PDEs: Application to Dirichlet-to-Neumann Problems. - Ferenc Izsák; Taki Eddine Djebbar (Algorithms, 2023)

Method of fundamental solutions: New approximation results and applications. - Hieu T. Hoang; Ferenc Izsák; Gábor Maros (J. Comput. Appl. Math., 2024)

On the computation of the gradient in implicit neural networks. - Béla J. Szekeres; Ferenc Izsák (J. Supercomput., 2024)