dr hab. Przemysław Spurek, prof. UJ
Jednostki:
- Wydział Matematyki i Informatyki UJ
- Instytut Informatyki i Matematyki Komputerowej
- Katedra Uczenia Maszynowego
Doktorat Otwarcie: 2012-05-31, Zamknięcie: 2014-06-26
Publikacje:
79.
HyperMask: Adaptive hypernetwork-based masks for continual learning, Neural Networks vol. 191 (2025), 107736
78.
Łukasz Struski, Tomasz Urbańczyk, Krzysztof Bucki, Bartłomiej Cupiał, Aneta Kaczyńska, Przemysław Spurek, Jacek Tabor
MeVGAN: GAN-based plugin model for video generation with applications in colonoscopy, PLoS One vol. 20 (5) (2025), e0312038
77.
Patryk Krukowski, Anna Bielawska, Kamil Książek, Paweł Wawrzynski , Paweł Batorski, Przemysław Spurek
76.
Piotr Borycki, Kubacki Piotr, Marcin Przewięźlikowski, Tomasz Kuśmierczyk, , Jacek Tabor
Hypernetwork Approach to Bayesian MAML (Student Abstract), National Conference of the American Association for Artificial Intelligence [AAAI] vol. 39 (2025), 29325-29327
75.
Mateusz Poleski, Jacek Tabor, Przemysław Spurek
GeoGuide: Geometric Guidance of Diffusion Models, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 1 (2025), 297-305
74.
CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression, IEEE International Joint Conference on Neural Networks [IJCNN](MAIN), (2025), accepted
73.
Dominik Zimny, Artur Kasymov, Adam Kania, Jacek Tabor, Maciej Zięba, Marcin Mazur, Przemysław Spurek
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation, Expert Systems with Applications vol. 279 (2025), 127350
72.
NegGS: Negative Gaussian Splatting, Information Sciences vol. 702 (2025), 121912
71.
Gaussian Splatting with NeRF-based color and opacity, Computer Vision and Image Understanding vol. 251 (2025), 104273
70.
Joanna Waczyńska, Piotr Borycki, Sławomir K. Tadeja, Joanna Kaleta, Przemysław Spurek
D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup, Advances in Neural Information Processing Systems [NeurIPS] vol. 37 (2025), 107865--107889
69.
Zięba Maciej , Marcin Przewięźlikowski, Marek Śmieja, Jacek Tabor, Tomasz Trzciński, Przemysław Spurek
RegFlow: Probabilistic Flow-Based Regression for Future Prediction, Asian Conference on Intelligent Information and Database Systems [ACIIDS], (2024), 267–279
68.
Marcin Przewięźlikowski, Przemysław Przybysz, Zięba Maciej , Jacek Tabor, Przemysław Spurek
HyperMAML: Few-shot adaptation of deep models with hypernetworks, Neurocomputing vol. 598 (2024), 128-179
67.
Przemysław Spurek, Tomasz Trzciński, Joanna Waczyńska, Dominik Zimny
Points2NeRF: Generating Neural Radiance Fields from 3D point cloud, Pattern Recognition Letters vol. 185 (2024), 8-14
66.
NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering, International Conference on Computational Science [ICCS](MAIN) vol. 14832 (2024), 346--361
65.
Przemysław Spurek, Sebastian Winczowski, Zięba Maciej , Tomasz Trzcinski, Kacper Kania, Marcin Mazur
Modeling 3D Surfaces with a Locally Conditioned Atlas, International Conference on Computational Science [ICCS](MAIN) vol. 14833 (2024), 100-115
64.
Gaussian model for closed curves, Expert Systems with Applications vol. 249 part B (2024), 123615
63.
Łukasz Struski, Paweł Morkisz, Przemysław Spurek, Samuel Rodriguez Bernabeu, Tomasz Trzciński
Efficient GPU implementation of randomized SVD and its applications, Expert Systems with Applications vol. 248 (2024), 123462
62.
Face Identity-Aware Disentanglement in StyleGAN, IEEE Workshop on Applications of Computer Vision [WACV], (2024), 5222-5231
61.
Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemysław Spurek
HyperCube: Implicit Field Representations of Voxelized 3D Models (Student Abstract), National Conference of the American Association for Artificial Intelligence [AAAI] vol. 38 (2024), 23623-23625
60.
Przemysław Spurek, Karol Piczak, Jacek Tabor, Tomasz Trzciński, Filip Szatkowski
Hypernetworks build Implicit Neural Representations of Sounds, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. 14172 (2023), 661–676
59.
Przemysław Spurek, Marcin Sendera, Marcin Przewięźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor
58.
Bounding Evidence and Estimating Log-Likelihood in VAE, International Conference on Artificial Intelligence and Statistics [AISTATS](MAIN) vol. 206 (2023), 5036-5051
57.
Przemysław Spurek, Jacek Tabor, Marcin Sendera, Marcin Przewięźlikowski, Konrad Karanowski, Zięba Maciej
Hypershot: Few-shot learning by kernel hypernetworks, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 2469--2478
56.
Przemysław Spurek, Przemysław Stachura, Ivan Kostiuk, Sławomir K. Tadeja, Tomasz Trzciński
55.
54.
Przemysław Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Sławomir K. Tadeja, Łukasz Struski, Jacek Tabor, Tomasz Trzciński
HyperPocket: generative point cloud completion, IEEE/RSJ International Conference on Intelligent Robots and Systems [IROS], (2022), 6848-6853
53.
Batch size reconstruction-distribution trade-off in kernel based generative autoencoders, IEEE International Conference on Image Processing [ICIP], (2022), 3728-3732
52.
Nonlinear Weighted Independent Component Analysis, International Conference on Information Processing and Management of Uncertainty [IPMU] vol. II (2022), 3–16
51.
Target layer regularization for continual learning using Cramer-Wold distance, Information Sciences vol. 609 (2022), 1369-1380
50.
Przemysław Spurek, Jacek Tabor, Piotr Tempczyk, Rafał Michaluk, Łukasz Garncarek, Adam Golinski
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood, International Conference on Machine Learning [ICML](MAIN), (2022), 21205-21231
49.
Jacek Tabor, Maciej Wołczyk, Karol Piczak, Bartosz Wójcik, Łukasz Pustelnik, Morawiecki Paweł, Tomasz Trzcinski, Przemysław Spurek
Continual Learning with Guarantees via Weight Interval Constraints, International Conference on Machine Learning [ICML](MAIN), (2022), 23897-23911
48.
LocoGAN—Locally convolutional GAN, Computer Vision and Image Understanding vol. 221 (2022), 103462
47.
Generative models with kernel distance in data space, Neurocomputing vol. 487 (2022), 119-129
46.
45.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński
44.
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders, International Conference on Tools with Artificial Intelligence [ICTAI], (2021), 1322-1326
43.
Missing Glow Phenomenon: learning disentangled representation of missing data, International Conference on Neural Information Processing [ICONIP] vol. vol 1516 (2021), 196-204
42.
Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Przemysław Spurek, Tomasz Trzciński, Zięba Maciej
Non-Gaussian Gaussian Processes for Few-Shot Regression, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. 34 (2021), 10285-10298
41.
Karol Piczak, Michał Sadowski, Przemysław Spurek, Tomasz Trzciński
Continual Learning of 3D Point Cloud Generators, International Conference on Neural Information Processing [ICONIP] vol. vol 13108 (2021), 330-341
40.
Kamil Deja, Jan Dubiński, Piotr Nowak, Przemysław Spurek, Tomasz Trzciński, Sandro Wenzel
End-to-End Sinkhorn Autoencoder With Noise Generator, IEEE Access vol. 9 (2021), 7211-7219
39.
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models, European Symposium on Artificial Neural Networks [ESANN], (2020), 6
38.
Processing of Incomplete Images by (Graph) Convolutional Neural Networks, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science, volume 12533 (2020), 512-523
37.
Tomasz Danel, Przemysław Spurek, Jacek Tabor, Marek Śmieja, Łukasz Struski, Agnieszka Słowik, Łukasz Maziarka
Spatial Graph Convolutional Networks, International Conference On Neural Information Processing vol. Communications in Computer and Information Science book series (CCIS, volume 1333) (2020), 668-675
36.
Non-linear ICA based on Cramer-Wold metric, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 12534) (2020),
35.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński, Sebastian Winczowski, Maciej Zamorski
Hypernetwork approach to generating point clouds, International Conference on Machine Learning [ICML](MAIN), (2020),
34.
Cramer-Wold Auto-Encoder, Journal of Machine Learning Research vol. 21 (2020), 1-28
33.
Processing of incomplete images by (graph) convolutional neural networks, International Conference On Machine Learning (workshop Track) (2020),
32.
Flow-based SVDD for anomaly detection, International Conference On Machine Learning (workshop Track) (2020),
31.
Set Aggregation Network as a Trainable Pooling Layer, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 11954) (2019), 419-431
30.
Projected memory clustering, Pattern Recognition Letters vol. 123 (2019), 9-15
29.
Online updating of active function cross-entropy clustering, Pattern Analysis and Applications vol. vol. 22 no. 4 (2019), 1409-1425
28.
SVM with a neutral class, Pattern Analysis and Applications vol. 22/2 (2019), 573-582
27.
Image Stitching Based on Entropy Minimization, Schedae Informaticae vol. 27 (2018), 129-141
26.
Sliced generative models, Schedae Informaticae vol. 27 (2018), 69-79
25.
24.
Processing of missing data by neural networks, Advances in Neural Information Processing Systems vol. 31 (2018), 2719-2729
23.
Lossy Compression Approach to Subspace Clustering, Information Sciences vol. 435 (2018), 161-183
22.
Monika Brzychczy-Włoch, Krzysztof Misztal, Dorota Ochońska, Anna Plichta, Przemysław Spurek, Bartosz Zieliński
Deep learning approach to bacterial colony classification, PLoS One vol. 12 (9) (2017), 1-14
21.
Split-and-merge Tweak in Cross Entropy Clustering, Computer Information Systems and Industrial Management: 16th Ifip Tc8 International Conference (2017), 193 - 204
20.
Uniform Cross-entropy Clustering, Schedae Informaticae vol. 25 (2017), 117-126
19.
ICA based on asymmetry, Pattern Recognition vol. 67 (2017), 230-244
18.
Active Function Cross-Entropy Clustering, Expert Systems with Applications vol. 72 (2017), 49–66
17.
R Package CEC , Neurocomputing vol. 237 (2017), 410–413
16.
General Split Gaussian Cross-Entropy Clustering, Expert Systems with Applications vol. 68 (2017), 58–68
15.
Maximum Likelihood Estimation and Optimal Coordinates, International Conference On Systems Science, 2016 vol. Springer (2016), 3-13
14.
Clustering of Gaussian distributions, 2016 International Joint Conference On Neural Networks (ijcnn) vol. IEEE (2016), 3346-3353
13.
12.
Cross-Entropy based image thresholding, Schedae Informaticae vol. 24 (2015), 21-29
11.
10.
Subspace memory clustering, Schedae Informaticae vol. 24 (2015), 133-142
9.
Przemysław Spurek, Jacek Tabor, Mateusz Wójcik
Cross-Entropy Clustering Approach to One-Class Classification, Lecture Notes in Computer Science vol. 9119 (2015), 481-490
8.
Przemysław Spurek, Elżbieta Zając
Metody analizy mikroskopowych obrazów warstw C-Pd, (2014), "Świat nanotechnologii. Warstwy nanokompozytowe węglowo-palladowe. Badania i technologia", Wydawnictwa Uniwersytetu Warszawskiego
7.
Alena Chaikouskaya, Przemysław Spurek, Jacek Tabor, Elżbieta Zając
A local Gaussian filter and adaptive morphology as tools for completing partially discontinuous curves, Computer Information Systems and Industrial Management vol. 8838 (2014), 559-570
6.
5.
Cross Entropy Clustering, Pattern Recognition vol. 47 (2014), 3046–3059
4.
Weighted Approach to Projective Clustering, Computer Information Systems and Industrial Management Lecture Notes in Computer Science vol. 8104 (2013), 367-378
3.
The memory center, Information Sciences vol. 252 (2013), 132–143
2.
Przemysław Spurek, Jacek Tabor, Elżbieta Zając
Detection of Disk-Like Particles in Electron Microscopy Images, Advances in Intelligent Systems and Computing vol. 226 (2013), 411-417
1.
Konferencje organizowane:
2.
Theoretical Foundations of Machine Learning - TFML 2017, Kraków, 2017-02-13, 2017-02-17
1.
Theoretical Foundations of Machine Learning, Będlewo, 2015-02-16, 2015-02-20
Granty (realizowane po maju 2009 roku)
| Tytuł | Rola | Rozpoczęcie | Zakończenie |
|---|---|---|---|
| Środek ciężkości pamięci | Kierownik | 2014-02-24 | 2016-08-23 |
| Paradygmat minimalizacji pamięci w klastrowaniu | Wykonawca | 2015-01-21 | 2017-08-26 |
| Budowanie algorytmów grupowania danych w oparciu o uogólnione rozkłady normalne oraz rozkłady nie gaussowskie | Kierownik | 2016-06-13 | 2020-06-12 |
| Generowanie rzeczywistych obrazów za pomocą modeli opartych na architekturze autoenkodera | Kierownik | 2020-02-20 | 2023-08-19 |
| Hipersieci w metodach głębokiego metauczenia | Kierownik | 2022-07-04 | 2026-07-03 |
| Modele generatywne 3D oparte na reprezentacji NeRF | Kierownik | 2024-08-01 | 2028-07-31 |