Maciej Ziȩba

发表

HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks

J. Tabor, P. Spurek, Marcin Przewiezlikowski, 2022, ArXiv.

Two-headed eye-segmentation approach for biometric identification

T. Jeanneau, Maciej Ziȩba, Wiktor Lazarski, 2022, ArXiv.

Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation

M. Pantic, Stavros Petridis, Konstantinos Vougioukas, 2023, arXiv.org.

Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction

Jakub M. Tomczak, Maciej Zieba, Sebastian K. Tomczak, 2016, Expert Syst. Appl..

Self-paced Learning for Imbalanced Data

Jakub M. Tomczak, Maciej Zieba, Jerzy Swiatek, 2016, ACIIDS.

Probabilistic combination of classification rules and its application to medical diagnosis

Jakub M. Tomczak, Maciej Zieba, Maciej Ziȩba, 2015, Machine Learning.

HyperShot: Few-Shot Learning by Kernel HyperNetworks

J. Tabor, P. Spurek, Marcin Przewiezlikowski, 2022, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Adversarial autoencoders for compact representations of 3D point clouds

Piotr Klukowski, Maciej Zięba, Wojciech Stokowiec, 2018, Comput. Vis. Image Underst..

Hypernetwork approach to generating point clouds

T. Trzciński, J. Tabor, P. Spurek, 2020, ICML.

BinGAN: Learning Compact Binary Descriptors with a Regularized GAN

Tomasz Trzcinski, Tarek El-Gaaly, Maciej Zieba, 2018, NeurIPS.

UCSG-Net - Unsupervised Discovering of Constructive Solid Geometry Tree pdf

Maciej Zieba, Tomasz Kajdanowicz, Kacper Kania, 2020, NeurIPS.

NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering

J. Tabor, P. Spurek, Maciej Ziȩba, 2023, ICCS.

On some method for limited services selection

Maciej Zieba, Agnieszka Prusiewicz, Maciej Ziȩba, 2011, Int. J. Intell. Inf. Database Syst..

The general framework for few-shot learning by kernel HyperNetworks

J. Tabor, P. Spurek, Marcin Przewiezlikowski, 2023, Machine Vision and Applications.

Probabilistic combination of classification rules and its application to medical diagnosis

Jakub M. Tomczak, Maciej Ziȩba, 2015, Machine Learning.

Classification Restricted Boltzmann Machine for comprehensible credit scoring model

Jakub M. Tomczak, Maciej Zieba, Maciej Ziȩba, 2015, Expert Syst. Appl..

Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients

Marek Lubicz, Jakub M. Tomczak, Maciej Zieba, 2014, Appl. Soft Comput..

On-line bayesian context change detection in web service systems

Jakub M. Tomczak, Maciej Zieba, Maciej Zieba, 2013, HotTopiCS '13.

Service-Oriented Medical System for Supporting Decisions With Missing and Imbalanced Data

Maciej Zieba, Maciej Ziȩba, 2014, IEEE Journal of Biomedical and Health Informatics.

The Proposal of Service Oriented Data Mining System for Solving Real-Life Classification and Regression Problems

Maciej Zieba, Agnieszka Prusiewicz, Maciej Ziȩba, 2011, DoCEIS.

NMRNet: a deep learning approach to automated peak picking of protein NMR spectra

Piotr Klukowski, Adam Gonczarek, Michal J. Walczak, 2018, Bioinform..

RBM-SMOTE: Restricted Boltzmann Machines for Synthetic Minority Oversampling Technique

Jakub M. Tomczak, Adam Gonczarek, Maciej Zieba, 2015, ACIIDS.

HyperNeRFGAN: Hypernetwork approach to 3D NeRF GAN

P. Spurek, Maciej Ziȩba, A. Kasymov, 2023, ArXiv.

Gaussian process regression for automated signal tracking in step-wise perturbed Nuclear Magnetic Resonance spectra

Adam Gonczarek, Maciej Zieba, Piotr Klukowski, 2018, Appl. Soft Comput..

Continual learning on 3D point clouds with random compressed rehearsal

Maciej Zieba, M. Zamorski, Tomasz Trzci'nski, 2022, Comput. Vis. Image Underst..

RegFlow: Probabilistic Flow-based Regression for Future Prediction pdf

Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek, 2020, SSRN Electronic Journal.

MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation

J. Tabor, P. Spurek, Maciej Ziȩba, 2023, ArXiv.

Generative Adversarial Networks: recent developments

Maciej Zieba, Jerzy Swiatek, Maciej Zamorski, 2019, ICAISC.

TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression

Maciej Ziȩba, Patryk Wielopolski, 2022, arXiv.org.

The general framework for few-shot learning by kernel HyperNetworks

J. Tabor, P. Spurek, Marcin Przewiezlikowski, 2023, Machine Vision and Applications.

General Hypernetwork Framework for Creating 3D Point Clouds

T. Trzciński, J. Tabor, P. Spurek, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Training Triplet Networks with GAN pdf

Lei Wang, Maciej Zieba, Lei Wang, 2017, ICLR.

Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation

M. Pantic, Stavros Petridis, Konstantinos Vougioukas, 2023, ArXiv.

Non-Gaussian Gaussian Processes for Few-Shot Regression pdf

Jacek Tabor, Przemyslaw Spurek, Massimiliano Patacchiola, 2021, NeurIPS.

Post-training Quantization Methods for Deep Learning Models

Maciej Zieba, Piotr Kluska, P. Kluska, 2020, ACIIDS.

Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks

A. Gonczarek, Maciej Ziȩba, M. Baran, 2023, ACL.

PluGeN: Multi-Label Conditional Generation From Pre-Trained Models pdf

Marek Smieja, Maciej Zieba, Lukasz Maziarka, 2021, AAAI.

Boosted SVM with active learning strategy for imbalanced data

Jakub M. Tomczak, Maciej Zieba, Maciej Ziȩba, 2014, Soft Computing.

Self-supervised adversarial masking for 3D point cloud representation learning

Michal Stypulkowski, Maciej Ziȩba, Michal Szachniewicz, 2023, ArXiv.

Generative Modeling in Application to Point Cloud Completion

Maciej Zieba, Jerzy Swiatek, Maciej Zamorski, 2020, ICAISC.

Adversarial Autoencoders for Generating 3D Point Clouds pdf

Tomasz Trzcinski, Wojciech Stokowiec, Maciej Zieba, 2018, ArXiv.

Services Recommendation in Systems Based on Service Oriented Architecture by Applying Modified ROCK Algorithm

Maciej Zięba, Agnieszka Prusiewicz, Maciej Ziȩba, 2010, NDT.

HyperFlow: Representing 3D Objects as Surfaces pdf

Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek, 2020, ArXiv.