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Gašper Petelin
Gašper Petelin
Unknown affiliation
Verified email at ijs.si
Title
Cited by
Cited by
Year
DSCTool: A web-service-based framework for statistical comparison of stochastic optimization algorithms
T Eftimov, G Petelin, P Korošec
Applied Soft Computing 87, 105977, 2020
372020
HZDR Multiphase Addon for OpenFOAM
F Schlegel, G Petelin, M Tekavčič
Institut Jožef Stefan, 2021
162021
Multi-objective approaches to ground station scheduling for optimization of communication with satellites
G Petelin, M Antoniou, G Papa
Optimization and Engineering 24 (1), 147-184, 2023
132023
Towards understanding the importance of time-series features in automated algorithm performance prediction
G Petelin, G Cenikj, T Eftimov
Expert Systems with Applications 213, 119023, 2023
102023
Tla: Topological landscape analysis for single-objective continuous optimization problem instances
G Petelin, G Cenikj, T Eftimov
2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1698-1705, 2022
62022
Less is more: Selecting the right benchmarking set of data for time series classification
T Eftimov, G Petelin, G Cenikj, A Kostovska, G Ispirova, P Korošec, ...
Expert Systems with Applications 198, 116871, 2022
62022
DynamoRep: trajectory-based population dynamics for classification of black-box optimization problems
G Cenikj, G Petelin, C Doerr, P Korošec, T Eftimov
Proceedings of the Genetic and Evolutionary Computation Conference, 813-821, 2023
52023
On formulating the ground scheduling problem as a multi-objective bilevel problem
M Antoniou, G Petelin, G Papa
International Conference on Bioinspired Methods and Their Applications, 177-188, 2020
32020
PerformViz: a machine learning approach to visualize and understand the performance of single-objective optimization algorithms
T Eftimov, R Hribar, U Škvorc, G Popovski, G Petelin, P Korošec
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
32020
Deep statistics: more robust performance statistics for single-objective optimization benchmarking
T Eftimov, G Petelin, R Hribar, G Popovski, U Škvorc, P Korošec
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
32020
TransOpt: Transformer-based Representation Learning for Optimization Problem Classification
G Cenikj, G Petelin, T Eftimov
arXiv preprint arXiv:2311.18035, 2023
12023
Models for forecasting the traffic flow within the city of Ljubljana
G Petelin, R Hribar, G Papa
European Transport Research Review 15 (1), 30, 2023
12023
Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem
R Hribar, T Hrga, G Papa, G Petelin, J Povh, N Pržulj, V Vukašinović
Journal of Global Optimization 82 (2), 283-312, 2022
12022
Preferred solutions of the ground station scheduling problem using NSGA-III with weighted reference points selection
M Antoniou, G Petelin, G Papa
2021 IEEE Congress on Evolutionary Computation (CEC), 1840-1847, 2021
12021
Podatkovno vodena inicializacija uteži nevronskih mrež
G Petelin
Univerza v Ljubljani, Fakulteta za računalništvo in informatiko, 2020
12020
GPU-based Accelerated Computation of Coalescence and Breakup Frequencies for Polydisperse Bubbly Flows
G Petelin, R Lehnigk, J Kelling, G Papa, F Schlegel
1
A cross-benchmark examination of feature-based algorithm selector generalization in single-objective numerical optimization
G Cenikj, G Petelin, T Eftimov
Swarm and Evolutionary Computation 87, 101534, 2024
2024
TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting
G Petelin, G Cenikj, T Eftimov
Swarm and Evolutionary Computation 84, 101448, 2024
2024
How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms?
G Petelin, G Cenikj
2023 IEEE Symposium Series on Computational Intelligence (SSCI), 341-346, 2023
2023
Dealing with zero-inflated data: achieving SOTA with a two-fold machine learning approach
JM Rožanec, G Petelin, J Costa, B Bertalanič, G Cerar, M Guček, G Papa, ...
arXiv preprint arXiv:2310.08088, 2023
2023
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