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Paweł Liskowski
Paweł Liskowski
Research Scientist, NNAISENSE
Verified email at nnaisense.com - Homepage
Title
Cited by
Cited by
Year
Segmenting Retinal Blood Vessels With Deep Neural Networks
P Liskowski, K Krawiec
IEEE transactions on medical imaging 35 (11), 2369-2380, 2016
9682016
Learning to Play Othello With Deep Neural Networks
P Liskowski, W Jaśkowski, K Krawiec
IEEE Transactions on Games 10 (4), 354-364, 2018
382018
Comparison of semantic-aware selection methods in genetic programming
P Liskowski, K Krawiec, T Helmuth, L Spector
Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015
362015
Automatic derivation of search objectives for test-based genetic programming
K Krawiec, P Liskowski
European Conference on Genetic Programming, 53-65, 2015
292015
Improving coevolution by random sampling
W Jaśkowski, P Liskowski, M Szubert, K Krawiec
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
202013
Discovery of implicit objectives by compression of interaction matrix in test-based problems
P Liskowski, K Krawiec
Parallel Problem Solving from Nature–PPSN XIII: 13th International …, 2014
162014
Online discovery of search objectives for test-based problems
P Liskowski, K Krawiec
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference …, 2016
152016
High-dimensional function approximation for knowledge-free reinforcement learning: a case study in SZ-Tetris
W Jaśkowski, M Szubert, P Liskowski, K Krawiec
Proceedings of the 2015 Annual Conference on Genetic and Evolutionary …, 2015
152015
Non-negative matrix factorization for unsupervised derivation of search objectives in genetic programming
P Liskowski, K Krawiec
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 749-756, 2016
142016
Shaping fitness function for evolutionary learning of game strategies
M Szubert, W Jaśkowski, P Liskowski, K Krawiec
Proceedings of the 15th annual conference on genetic and evolutionary …, 2013
122013
Clipup: a simple and powerful optimizer for distribution-based policy evolution
NE Toklu, P Liskowski, RK Srivastava
International Conference on Parallel Problem Solving from Nature, 515-527, 2020
102020
Program synthesis as latent continuous optimization: Evolutionary search in neural embeddings
P Liskowski, K Krawiec, NE Toklu, J Swan
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 359-367, 2020
102020
Surrogate fitness via factorization of interaction matrix
P Liskowski, K Krawiec
Genetic Programming: 19th European Conference, EuroGP 2016, Porto, Portugal …, 2016
92016
Neuro-guided genetic programming: prioritizing evolutionary search with neural networks
P Liskowski, I Błądek, K Krawiec
Proceedings of the Genetic and Evolutionary Computation Conference, 1143-1150, 2018
72018
Discovery of search objectives in continuous domains
P Liskowski, K Krawiec
Proceedings of the Genetic and Evolutionary Computation Conference, 969-976, 2017
72017
Multi-criteria comparison of coevolution and temporal difference learning on Othello
W Jaśkowski, M Szubert, P Liskowski
Applications of Evolutionary Computation: 17th European Conference …, 2014
72014
The performance profile: A multi-criteria performance evaluation method for test-based problems
W Jaśkowski, P Liskowski, M Szubert, K Krawiec
International Journal of Applied Mathematics and Computer Science 26 (1 …, 2016
52016
The role of behavioral diversity and difficulty of opponents in coevolving game-playing agents
M Szubert, W Jaśkowski, P Liskowski, K Krawiec
Applications of Evolutionary Computation: 18th European Conference …, 2015
52015
Adaptive test selection for factorization-based surrogate fitness in genetic programming
K Krawiec, P Liskowski
Foundations of Computing and Decision Sciences 42 (4), 339-358, 2017
32017
EvoTorch: Scalable Evolutionary Computation in Python
NE Toklu, T Atkinson, V Micka, P Liskowski, RK Srivastava
arXiv preprint arXiv:2302.12600, 2023
22023
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