Követés
Barbara Barabasz
Barbara Barabasz
Ismeretlen szervezet
Nincs ellenőrzött e-mail-cím
Cím
Hivatkozott rá
Hivatkozott rá
Év
Multi-deme, twin adaptive strategy hp-HGS
B Barabasz, S Migórski, R Schaefer, M Paszyński
Inverse Problems in Science and Engineering 19 (1), 3-16, 2011
292011
Error analysis and improving the accuracy of Winograd convolution for deep neural networks
B Barabasz, A Anderson, KM Soodhalter, D Gregg
ACM Transactions on Mathematical Software (TOMS) 46 (4), 1-33, 2020
272020
A hybrid algorithm for solving inverse problems in elasticity
B Barabasz, E Gajda-Zagórska, S Migórski, M Paszyński, R Schaefer, ...
International Journal of Applied Mathematics and Computer Science 24 (4 …, 2014
272014
Efficient adaptive strategy for solving inverse problems
M Paszyński, B Barabasz, R Schaefer
Computational Science–ICCS 2007: 7th International Conference, Beijing …, 2007
242007
Winograd convolution for dnns: Beyond linear polynomials
B Barabasz, D Gregg
International Conference of the Italian Association for Artificial …, 2019
182019
Winograd convolution for deep neural networks: Efficient point selection
SA Alam, A Anderson, B Barabasz, D Gregg
ACM Transactions on Embedded Computing Systems 21 (6), 1-28, 2022
162022
Asymptotic Behavior of hp–HGS (hp–Adaptive Finite Element Method Coupled with the Hierarchic Genetic Strategy) by Solving Inverse Problems
R Schaefer, B Barabasz
International Conference on Computational Science, 682-691, 2008
142008
Quantaized winograd/toom-cook convolution for dnns: Beyond canonical polynomials base
B Barabasz
arXiv preprint arXiv:2004.11077, 2020
62020
Studying inverse problems in elasticity by hierarchic genetic search
B Barabasz, E Gajda, S Migórski, M Paszynski, R Schaefer
ECCOMAS thematic conference on Inverse Problems in Mechanics of Structures …, 2011
52011
Handling Ambiguous Inverse Problems by the Adaptive Genetic Strategy hp–HGS
B Barabasz, R Schaefer, M Paszyński
International Conference on Computational Science, 904-913, 2009
52009
Twin adaptive scheme for solving inverse problems
R Schaefer, B Barabasz, M Paszyński
Prace Naukowe Politechniki Warszawskiej. Elektronika, 241-249, 2007
52007
Speeding up multi-objective optimization of liquid fossil fuel reserve exploitation with parallel hybrid memory integration
B Barabasz, S Barrett, L Siwik, M Ło¶, K Podsiadło, M WoĽniak
Journal of Computational Science 31, 126-136, 2019
42019
Hardware and software performance in deep learning
A Anderson, J Garland, Y Wen, B Barabasz, K Persand, A Vasudevan, ...
by Geoff V. Merrett Bashir M. Al-Hashimi. Computing. Institution of …, 2019
32019
Coupled isogeometric finite element method and hierarchical genetic strategy with balanced accuracy for solving optimization inverse problem
B Barabasz, M Ło¶, M WoĽniak, L Siwik, S Barrett
Procedia Computer Science 108, 828-837, 2017
32017
Solving inverse problems by the multi-deme hierarchic genetic strategy
R Schaefer, B Barabasz, M Paszynski
2009 IEEE Congress on Evolutionary Computation, 3157-3163, 2009
32009
Asymptotic guarantee of success of the hp–HGS strategy
R Schaefer, B Barabasz, M Paszynski
22008
Optimization of production chains using the nature-inspired techniques
A Stanislawczyk, P Forys, L Sztangret, B Barabasz, J Kusiak
Steel Research International 2, 617-624, 2008
22008
Winograd Convolution for Deep Neural Networks: Efficient Point Selection
S Asad Alam, A Anderson, B Barabasz, D Gregg
arXiv e-prints, arXiv: 2201.10369, 2022
2022
hp-HGS twin adaptive strategy for inverse resistivity logging measurements
B Barabasz, E Gajda, D Pardo, M Paszyński, R Schaefer, D Szeliga
2011
An algorithm for relating convergence ratios of inverse and direct problem solutions by means of the self-adaptive hp finite element method
M Paszyński, D Szeliga, B Barabasz, P Macioł
CMM-2007 : 17th international conference on Computer Methods in Mechanics, 2007
2007
A rendszer jelenleg nem tudja elvégezni a műveletet. Próbálkozzon újra később.
Cikkek 1–20