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Łukasz Struski
Tytuł
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Processing of missing data by neural networks
M Śmieja, Ł Struski, J Tabor, B Zieliński, P Spurek
Advances in neural information processing systems 31, 2018
892018
Spatial graph convolutional networks
T Danel, P Spurek, J Tabor, M Śmieja, Ł Struski, A Słowik, Ł Maziarka
International Conference on Neural Information Processing, 668-675, 2020
35*2020
A classification-based approach to semi-supervised clustering with pairwise constraints
M Śmieja, Ł Struski, MAT Figueiredo
Neural Networks 127, 193-203, 2020
262020
Generalized RBF kernel for incomplete data
M Śmieja, Ł Struski, J Tabor, M Marzec
Knowledge-Based Systems 173, 150-162, 2019
262019
Generalized RBF kernel for incomplete data
M Śmieja, Ł Struski, J Tabor, M Marzec
Knowledge-Based Systems 173, 150-162, 2019
262019
Lossy compression approach to subspace clustering
Ł Struski, J Tabor, P Spurek
Information Sciences 435, 161-183, 2018
172018
Protopshare: Prototypical parts sharing for similarity discovery in interpretable image classification
D Rymarczyk, Ł Struski, J Tabor, B Zieliński
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
82021
Protopshare: Prototype sharing for interpretable image classification and similarity discovery
D Rymarczyk, Ł Struski, J Tabor, B Zieliński
arXiv preprint arXiv:2011.14340, 2020
82020
Estimating conditional density of missing values using deep gaussian mixture model
M Przewięźlikowski, M Śmieja, Ł Struski
International Conference on Neural Information Processing, 220-231, 2020
72020
Semi-supervised model-based clustering with controlled clusters leakage
M Śmieja, Ł Struski, J Tabor
Expert Systems with Applications 85, 146-157, 2017
72017
Hyperpocket: Generative point cloud completion
P Spurek, A Kasymov, M Mazur, D Janik, S Tadeja, Ł Struski, J Tabor, ...
arXiv preprint arXiv:2102.05973, 2021
42021
Iterative imputation of missing data using auto-encoder dynamics
M Śmieja, M Kołomycki, Ł Struski, M Juda, MAT Figueiredo
International Conference on Neural Information Processing, 258-269, 2020
42020
Processing of incomplete images by (graph) convolutional neural networks
T Danel, M Śmieja, Ł Struski, P Spurek, Ł Maziarka
International Conference on Neural Information Processing, 512-523, 2020
42020
Can auto-encoders help with filling missing data?
M Śmieja, M Kołomycki, Ł Struski, M Juda, MAT Figueiredo
ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020
42020
Cone-fields without constant orbit core dimension
Ł Struski, J Tabor, T Kułaga
Discrete & Continuous Dynamical Systems 32 (10), 3651, 2012
42012
Pharmacoprint: A Combination of a Pharmacophore Fingerprint and Artificial Intelligence as a Tool for Computer-Aided Drug Design
D Warszycki, Ł Struski, M Smieja, R Kafel, R Kurczab
Journal of Chemical Information and Modeling 61 (10), 5054-5065, 2021
32021
Flow-based anomaly detection
Ł Maziarka, M Śmieja, M Sendera, Ł Struski, J Tabor, P Spurek
arXiv preprint arXiv:2010.03002, 2020
3*2020
Interpretable image classification with differentiable prototypes assignment
D Rymarczyk, Ł Struski, M Górszczak, K Lewandowska, J Tabor, ...
arXiv preprint arXiv:2112.02902, 2021
22021
Incomplete data representation for SVM classification
L Struski, M Smieja, J Tabor
arXiv preprint arXiv:1612.01480, 2016
22016
Expansivity and cone-fields in metric spaces
Ł Struski, J Tabor
Journal of Dynamics and Differential Equations 26 (3), 517-527, 2014
22014
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