Barbara Barabasz

According to our database, Barbara Barabasz authored at least 13 papers between 2007 and 2022.

Collaborative distances:

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

2022

Winograd Convolution for Deep Neural Networks: Efficient Point Selection.

Syed Asad Alam, Andrew Anderson, Barbara Barabasz, David Gregg

ACM Trans. Embed. Comput. Syst., November, 2022

2020

Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks.

Barbara Barabasz, Andrew Anderson, Kirk M. Soodhalter, David Gregg

ACM Trans. Math. Softw., 2020

Quantaized Winograd/Toom-Cook Convolution for DNNs: Beyond Canonical Polynomials Base.

Barbara Barabasz

CoRR, 2020

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

Winograd Convolution for DNNs: Beyond linear polinomials.

Barbara Barabasz, David Gregg

CoRR, 2019

Winograd Convolution for DNNs: Beyond Linear Polynomials.

Barbara Barabasz, David Gregg

Proceedings of the AI*IA 2019 - Advances in Artificial Intelligence, 2019

2018

Improving accuracy of Winograd convolution for DNNs.

Barbara Barabasz, Andrew Anderson, David Gregg

CoRR, 2018

2017

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

Proceedings of the International Conference on Computational Science, 2017

2014

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

2009

Handling Ambiguous Inverse Problems by the Adaptive Genetic Strategy hp-HGS.

Barbara Barabasz, Robert Schaefer, Maciej Paszynski

Proceedings of the Computational Science, 2009

Solving inverse problems by the multi-deme hierarchic genetic strategy.

Robert Schaefer, Barbara Barabasz, Maciej Paszynski

Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008

Asymptotic Behavior of hp-HGS (hp-Adaptive Finite Element Method Coupled with the Hierarchic Genetic Strategy) by Solving Inverse Problems.

Robert Schaefer, Barbara Barabasz

Proceedings of the Computational Science, 2008

2007

Efficient Adaptive Strategy for Solving Inverse Problems.

Maciej Paszynski, Barbara Barabasz, Robert Schaefer

Proceedings of the Computational Science, 2007