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2020 – today
- 2024
[j19]Patryk Wielopolski
, Oleksii Furman, Maciej Zieba:
NodeFlow: Towards End-to-End Flexible Probabilistic Regression on Tabular Data. Entropy 26(7): 593 (2024)- [j18]Wojciech Kozlowski, Michal Szachniewicz, Michal Stypulkowski, Maciej Zieba:
Dimma: Semi-Supervised Low-Light Image Enhancement with Adaptive Dimming. Entropy 26(9): 726 (2024) - [j17]Dan Bigioi, Shubhajit Basak, Michal Stypulkowski, Maciej Zieba, Hugh Jordan, Rachel McDonnell, Peter Corcoran:
Speech driven video editing via an audio-conditioned diffusion model. Image Vis. Comput. 142: 104911 (2024) - [j16]Magdalena Proszewska, Maciej Wolczyk, Maciej Zieba, Patryk Wielopolski, Lukasz Maziarka, Marek Smieja:
Multi-Label Conditional Generation From Pre-Trained Models. IEEE Trans. Pattern Anal. Mach. Intell. 46(9): 6185-6198 (2024) - [j15]Katarzyna Jablonska, Marcin Maksymowicz, Dariusz Tanajewski, Wojciech Kaczan, Maciej Zieba, Marek Wilgucki:
MineCam: Application of Combined Remote Sensing and Machine Learning for Segmentation and Change Detection of Mining Areas Enabling Multi-Purpose Monitoring. Remote. Sens. 16(6): 955 (2024) - [c36]Michal Szachniewicz, Wojciech Kozlowski, Michal Stypulkowski, Maciej Zieba:
Self-supervised Adversarial Masking for 3D Point Cloud Representation Learning. ACIIDS (2) 2024: 156-168 - [c35]Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba:
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. ECAI 2024: 954-961 - [c34]Przemyslaw Spurek, Sebastian Winczowski, Maciej Zieba, Tomasz Trzcinski, Kacper Kania, Marcin Mazur:
Modeling 3D Surfaces with a Locally Conditioned Atlas. ICCS (2) 2024: 100-115 - [c33]Wojciech Zajac, Joanna Waczynska, Piotr Borycki, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering. ICCS (1) 2024: 346-361 - [c32]Katarzyna Jablonska, Maciej Zieba:
A Comparative Analysis of Siamese Networks and Spectral Angle Mapper for Mineral Detection using Hyperspectral Imagery. IGARSS 2024: 9320-9323 - [c31]Michal Stypulkowski, Konstantinos Vougioukas, Sen He, Maciej Zieba, Stavros Petridis, Maja Pantic:
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation. WACV 2024: 5089-5098 - [i30]Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba:
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. CoRR abs/2405.17640 (2024) - [i29]Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba:
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels. CoRR abs/2405.17642 (2024) - 2023
- [j14]Paulina Wisniewska, Maciej Zieba:
Generic projections of the H4 configuration of points. Adv. Appl. Math. 142: 102432 (2023) - [j13]Maciej Zamorski, Michal Stypulkowski, Konrad Karanowski, Tomasz Trzcinski, Maciej Zieba:
Continual learning on 3D point clouds with random compressed rehearsal. Comput. Vis. Image Underst. 228: 103621 (2023) - [j12]Marcin Sendera, Marcin Przewiezlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek:
The general framework for few-shot learning by kernel HyperNetworks. Mach. Vis. Appl. 34(4): 53 (2023) - [c30]Patryk Wielopolski, Michal Koperski, Maciej Zieba:
Flow Plugin Network for Conditional Generation. ACIIDS (2) 2023: 221-232 - [c29]Mateusz Baran, Joanna Baran, Mateusz Wójcik, Maciej Zieba, Adam Gonczarek:
Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks. ACL (student) 2023: 119-129 - [c28]Patryk Wielopolski, Maciej Zieba:
TreeFlow: Going Beyond Tree-Based Parametric Probabilistic Regression. ECAI 2023: 2631-2638 - [c27]Piotr Milkowski, Konrad Karanowski, Patryk Wielopolski, Jan Kocon, Przemyslaw Kazienko, Maciej Zieba:
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows. ICDM (Workshops) 2023: 757-766 - [c26]Patryk Rygiel, Pawel Pluszka, Maciej Zieba, Tomasz K. Konopczynski:
CenterlinePointNet++: A New Point Cloud Based Architecture for Coronary Artery Pressure Drop and vFFR Estimation. MICCAI (7) 2023: 781-790 - [c25]Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek:
HyperShot: Few-Shot Learning by Kernel HyperNetworks. WACV 2023: 2468-2477 - [i28]Michal Stypulkowski, Konstantinos Vougioukas, Sen He, Maciej Zieba, Stavros Petridis, Maja Pantic:
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation. CoRR abs/2301.03396 (2023) - [i27]Adam Kania, Artur Kasymov, Maciej Zieba, Przemyslaw Spurek:
HyperNeRFGAN: Hypernetwork approach to 3D NeRF GAN. CoRR abs/2301.11631 (2023) - [i26]Wojciech Zajac, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering. CoRR abs/2303.06226 (2023) - [i25]Dominik Zimny, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation. CoRR abs/2305.10579 (2023) - [i24]Michal Szachniewicz, Wojciech Kozlowski, Michal Stypulkowski, Maciej Zieba:
Self-supervised adversarial masking for 3D point cloud representation learning. CoRR abs/2307.05325 (2023) - [i23]Mateusz Baran, Joanna Baran, Mateusz Wójcik, Maciej Zieba, Adam Gonczarek:
Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks. CoRR abs/2307.07002 (2023) - [i22]Wojciech Kozlowski, Michal Szachniewicz, Michal Stypulkowski, Maciej Zieba:
Dimma: Semi-supervised Low Light Image Enhancement with Adaptive Dimming. CoRR abs/2310.09633 (2023) - [i21]Piotr Milkowski, Konrad Karanowski, Patryk Wielopolski, Jan Kocon, Przemyslaw Kazienko, Maciej Zieba:
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows. CoRR abs/2312.06034 (2023) - 2022
- [j11]Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski:
General Hypernetwork Framework for Creating 3D Point Clouds. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9995-10008 (2022) - [c24]Maciej Wolczyk, Magdalena Proszewska, Lukasz Maziarka, Maciej Zieba, Patryk Wielopolski, Rafal Kurczab, Marek Smieja:
PluGeN: Multi-Label Conditional Generation from Pre-trained Models. AAAI 2022: 8647-8656 - [c23]Patryk Rygiel, Maciej Zieba, Tomasz K. Konopczynski:
Eigenvector Grouping for Point Cloud Vessel Labeling. GeoMedIA 2022: 72-84 - [c22]Pawel Lorek, Rafal Nowak, Tomasz Trzcinski, Maciej Zieba:
FlowHMM: Flow-based continuous hidden Markov models. NeurIPS 2022 - [i20]Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek:
HyperShot: Few-Shot Learning by Kernel HyperNetworks. CoRR abs/2203.11378 (2022) - [i19]Maciej Zamorski, Michal Stypulkowski, Konrad Karanowski, Tomasz Trzcinski, Maciej Zieba:
Continual learning on 3D point clouds with random compressed rehearsal. CoRR abs/2205.08013 (2022) - [i18]Marcin Przewiezlikowski, P. Przybysz, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks. CoRR abs/2205.15745 (2022) - [i17]Patryk Wielopolski, Maciej Zieba:
TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression. CoRR abs/2206.04140 (2022) - [i16]Wiktor Lazarski, Maciej Zieba, Tanguy Jeanneau, Tobias Zillig, Christian Brendel:
Two-headed eye-segmentation approach for biometric identification. CoRR abs/2209.15471 (2022) - 2021
- [j10]Michal Stypulkowski, Kacper Kania, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski, Jan Chorowski:
Representing point clouds with generative conditional invertible flow networks. Pattern Recognit. Lett. 150: 26-32 (2021) - [c21]Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemyslaw Spurek, Maciej Zieba:
Non-Gaussian Gaussian Processes for Few-Shot Regression. NeurIPS 2021: 10285-10298 - [i15]Przemyslaw Spurek, Sebastian Winczowski, Maciej Zieba, Tomasz Trzcinski, Kacper Kania:
Modeling 3D Surface Manifolds with a Locally Conditioned Atlas. CoRR abs/2102.05984 (2021) - [i14]Maciej Wolczyk, Magdalena Proszewska, Lukasz Maziarka, Maciej Zieba, Patryk Wielopolski, Rafal Kurczab, Marek Smieja:
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models. CoRR abs/2109.09011 (2021) - [i13]Patryk Wielopolski, Michal Koperski, Maciej Zieba:
Flow Plugin Network for conditional generation. CoRR abs/2110.04081 (2021) - [i12]Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemyslaw Spurek, Maciej Zieba:
Non-Gaussian Gaussian Processes for Few-Shot Regression. CoRR abs/2110.13561 (2021) - 2020
- [j9]Maciej Zamorski, Maciej Zieba, Piotr Klukowski, Rafal Nowak, Karol Kurach, Wojciech Stokowiec, Tomasz Trzcinski:
Adversarial autoencoders for compact representations of 3D point clouds. Comput. Vis. Image Underst. 193: 102921 (2020) - [c20]Piotr Kluska, Maciej Zieba:
Post-training Quantization Methods for Deep Learning Models. ACIIDS (1) 2020: 467-479 - [c19]Adrian Zdobylak, Maciej Zieba:
Semi-supervised Representation Learning for 3D Point Clouds. ACIIDS (1) 2020: 480-491 - [c18]Maciej Zamorski, Maciej Zieba, Jerzy Swiatek:
Comparison of Aggregation Functions for 3D Point Clouds Classification. ACIIDS (1) 2020: 504-513 - [c17]Maciej Zamorski, Maciej Zieba, Jerzy Swiatek:
Generative Modeling in Application to Point Cloud Completion. ICAISC (1) 2020: 292-302 - [c16]Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski:
Hypernetwork approach to generating point clouds. ICML 2020: 9099-9108 - [c15]Kacper Kania, Maciej Zieba, Tomasz Kajdanowicz:
UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry Tree. NeurIPS 2020 - [i11]Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski:
Hypernetwork approach to generating point clouds. CoRR abs/2003.00802 (2020) - [i10]Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski:
HyperFlow: Representing 3D Objects as Surfaces. CoRR abs/2006.08710 (2020) - [i9]Kacper Kania, Maciej Zieba, Tomasz Kajdanowicz:
UCSG-Net - Unsupervised Discovering of Constructive Solid Geometry Tree. CoRR abs/2006.09102 (2020) - [i8]Michal Stypulkowski, Kacper Kania, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski, Jan Chorowski:
Representing Point Clouds with Generative Conditional Invertible Flow Networks. CoRR abs/2010.11087 (2020) - [i7]Maciej Zieba, Marcin Przewiezlikowski, Marek Smieja, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
RegFlow: Probabilistic Flow-based Regression for Future Prediction. CoRR abs/2011.14620 (2020)
2010 – 2019
- 2019
- [c14]Maciej Zamorski, Maciej Zieba:
Semi-supervised Learning with Bidirectional GANs. ACIIDS (1) 2019: 649-660 - [c13]Maciej Zamorski, Adrian Zdobylak, Maciej Zieba, Jerzy Swiatek:
Generative Adversarial Networks: Recent Developments. ICAISC (1) 2019: 248-258 - [i6]Maciej Zamorski, Adrian Zdobylak, Maciej Zieba, Jerzy Swiatek:
Generative Adversarial Networks: recent developments. CoRR abs/1903.12266 (2019) - [i5]Michal Stypulkowski, Maciej Zamorski, Maciej Zieba, Jan Chorowski:
Conditional Invertible Flow for Point Cloud Generation. CoRR abs/1910.07344 (2019) - 2018
- [j8]Maciej Zieba, Piotr Klukowski, Adam Gonczarek, Yaroslav Nikolaev, Michal J. Walczak:
Gaussian process regression for automated signal tracking in step-wise perturbed Nuclear Magnetic Resonance spectra. Appl. Soft Comput. 68: 162-171 (2018) - [j7]Piotr Klukowski, Michal Augoff, Maciej Zieba, Maciej Drwal, Adam Gonczarek, Michal J. Walczak:
NMRNet: a deep learning approach to automated peak picking of protein NMR spectra. Bioinform. 34(15): 2590-2597 (2018) - [c12]Maciej Zieba, Piotr Semberecki, Tarek El-Gaaly, Tomasz Trzcinski:
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN. NeurIPS 2018: 3612-3622 - [i4]Maciej Zieba, Piotr Semberecki, Tarek El-Gaaly, Tomasz Trzcinski:
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN. CoRR abs/1806.06778 (2018) - [i3]Maciej Zamorski, Maciej Zieba, Rafal Nowak, Wojciech Stokowiec, Tomasz Trzcinski:
Adversarial Autoencoders for Generating 3D Point Clouds. CoRR abs/1811.07605 (2018) - [i2]Maciej Zamorski, Maciej Zieba:
Semi-supervised learning with Bidirectional GANs. CoRR abs/1811.11426 (2018) - 2017
- [c11]Maciej Zieba, Lei Wang:
Training Triplet Networks with GAN. ICLR (Workshop) 2017 - [i1]Maciej Zieba, Lei Wang:
Training Triplet Networks with GAN. CoRR abs/1704.02227 (2017) - 2016
- [j6]Maciej Zieba, Sebastian K. Tomczak, Jakub M. Tomczak:
Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction. Expert Syst. Appl. 58: 93-101 (2016) - [c10]Maciej Zieba, Jakub M. Tomczak, Jerzy Swiatek:
Self-paced Learning for Imbalanced Data. ACIIDS (1) 2016: 564-573 - 2015
- [j5]Jakub M. Tomczak, Maciej Zieba:
Classification Restricted Boltzmann Machine for comprehensible credit scoring model. Expert Syst. Appl. 42(4): 1789-1796 (2015) - [j4]Jakub M. Tomczak, Maciej Zieba:
Probabilistic combination of classification rules and its application to medical diagnosis. Mach. Learn. 101(1-3): 105-135 (2015) - [j3]Maciej Zieba, Jakub M. Tomczak:
Boosted SVM with active learning strategy for imbalanced data. Soft Comput. 19(12): 3357-3368 (2015) - [c9]Maciej Zieba, Jakub M. Tomczak, Adam Gonczarek:
RBM-SMOTE: Restricted Boltzmann Machines for Synthetic Minority Oversampling Technique. ACIIDS (1) 2015: 377-386 - 2014
- [j2]Maciej Zieba, Jakub M. Tomczak, Marek Lubicz, Jerzy Swiatek:
Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients. Appl. Soft Comput. 14: 99-108 (2014) - [c8]Maciej Zieba, Jakub M. Tomczak, Krzysztof Brzostowski:
Selecting right questions with Restricted Boltzmann Machines. ICSEng 2014: 227-232 - 2013
- [c7]Maciej Zieba, Jerzy Swiatek:
Ensemble SVM for imbalanced data and missing values in postoperative risk management. Healthcom 2013: 95-99 - [c6]Maciej Zieba, Jerzy Swiatek, Marek Lubicz:
Cost Sensitive SVM with Non-informative Examples Elimination for Imbalanced Postoperative Risk Management Problem. ICSS 2013: 305-314 - [c5]Jakub Mikolaj Tomczak, Maciej Zieba:
On-line bayesian context change detection in web service systems. HotTopiCS 2013: 3-10 - 2012
- [c4]Maciej Zieba, Jerzy Swiatek:
Ensemble Classifier for Solving Credit Scoring Problems. DoCEIS 2012: 59-66 - 2011
- [j1]Agnieszka Prusiewicz, Maciej Zieba:
On some method for limited services selection. Int. J. Intell. Inf. Database Syst. 5(5): 493-509 (2011) - [c3]Krzysztof Brzostowski, Maciej Zieba:
Analysis of Human Arm Motions Recognition Algorithms for System to Visualize Virtual Arm. ICSEng 2011: 422-426 - [c2]Agnieszka Prusiewicz, Maciej Zieba:
The Proposal of Service Oriented Data Mining System for Solving Real-Life Classification and Regression Problems. DoCEIS 2011: 83-90 - 2010
- [c1]Agnieszka Prusiewicz, Maciej Zieba:
Services Recommendation in Systems Based on Service Oriented Architecture by Applying Modified ROCK Algorithm. NDT (2) 2010: 226-238
Coauthor Index
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last updated on 2024-10-28 20:15 CET by the dblp team
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