Efficient Adaptive Strategy for Solving Inverse Problems. - Maciej Paszynski; Barbara Barabasz; Robert Schaefer (International Conference on Computational Science (1), 2007)

Asymptotic Behavior of hp-HGS (hp-Adaptive Finite Element Method Coupled with the Hierarchic Genetic Strategy) by Solving Inverse Problems. - Robert Schaefer; Barbara Barabasz (ICCS (3), 2008)

Solving inverse problems by the multi-deme hierarchic genetic strategy. - Robert Schaefer; Barbara Barabasz; Maciej Paszynski (IEEE Congress on Evolutionary Computation, 2009)

Handling Ambiguous Inverse Problems by the Adaptive Genetic Strategy hp-HGS. - Barbara Barabasz; Robert Schaefer; Maciej Paszynski (ICCS (2), 2009)

A hybrid algorithm for solving inverse problems in elasticity. - Barbara Barabasz; Ewa Gajda-Zagórska; Stanislaw Migórski; Maciej Paszynski; Robert Schaefer; Maciej Smolka (Int. J. Appl. Math. Comput. Sci., 2014)

Coupled isogeometric Finite Element Method and Hierarchical Genetic Strategy with balanced accuracy for solving optimization inverse problem. - Barbara Barabasz; Marcin Los; Maciej Wozniak; Leszek Siwik; Stephen Barrett (ICCS, 2017)

Improving accuracy of Winograd convolution for DNNs. - Barbara Barabasz; Andrew Anderson 001; David Gregg (CoRR, 2018)

Winograd Convolution for DNNs: Beyond Linear Polynomials. - Barbara Barabasz; David Gregg (AI*IA, 2019)

Winograd Convolution for DNNs: Beyond linear polinomials. - Barbara Barabasz; David Gregg (CoRR, 2019)

Speeding up multi-objective optimization of liquid fossil fuel reserve exploitation with parallel hybrid memory integration. - Barbara Barabasz; Stephen Barrett; Leszek Siwik; Marcin Los; Krzysztof Podsiadlo; Maciej Wozniak (J. Comput. Sci., 2019)

Quantaized Winograd/Toom-Cook Convolution for DNNs: Beyond Canonical Polynomials Base. - Barbara Barabasz (CoRR, 2020)

Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks. - Barbara Barabasz; Andrew Anderson 001; Kirk M. Soodhalter; David Gregg (ACM Trans. Math. Softw., 2020)

Winograd Convolution for Deep Neural Networks: Efficient Point Selection. - Syed Asad Alam; Andrew Anderson 001; Barbara Barabasz; David Gregg (ACM Trans. Embed. Comput. Syst., 2022)