Applications of Inverse Limits to Extensions of Operators and Approximation of Lipschitz Functions. - Jacek Tabor; David T. Yost (J. Approx. Theory, 2002)

k-means Approach to the Karhunen-Loeve Transform - Krzysztof Misztal; Przemyslaw Spurek; Jacek Tabor (CoRR, 2011)

A New Algorithm for Rotation Detection in Iris Pattern Recognition. - Krzysztof Misztal; Jacek Tabor; Khalid Saeed 001 (CISIM, 2012)

Weighted Approach to Rényi Entropy - Marek Smieja; Jacek Tabor (CoRR, 2012)

Partition Reduction for Lossy Data Compression Problem - Marek Smieja; Jacek Tabor (CoRR, 2012)

The memory centre - Przemyslaw Spurek; Jacek Tabor (CoRR, 2012)

Strict localization of eigenvectors and eigenvalues - Lukasz Struski; Jacek Tabor (CoRR, 2012)

A t-norm embedding theorem for fuzzy sets. - Jakub Bielawski; Jacek Tabor (Fuzzy Sets Syst., 2012)

Entropy of the Mixture of Sources and Entropy Dimension. - Marek Smieja; Jacek Tabor (IEEE Trans. Inf. Theory, 2012)

Mahalanobis Distance-Based Algorithm for Ellipse Growing in Iris Preprocessing. - Krzysztof Misztal; Jacek Tabor (CISIM, 2013)

Weighted Approach to Projective Clustering. - Przemyslaw Spurek; Jacek Tabor; Krzysztof Misztal (CISIM, 2013)

Image Segmentation with Use of Cross-Entropy Clustering. - Marek Smieja; Jacek Tabor (CORES, 2013)

Detection of Disk-Like Particles in Electron Microscopy Images. - Przemyslaw Spurek; Jacek Tabor; Elzbieta Zajac (CORES, 2013)

Detection of Elliptical Shapes via Cross-Entropy Clustering. - Jacek Tabor; Krzysztof Misztal (IbPRIA, 2013)

The memory center. - Przemyslaw Spurek; Jacek Tabor (Inf. Sci., 2013)

A Local Gaussian Filter and Adaptive Morphology as Tools for Completing Partially Discontinuous Curves. - Przemyslaw Spurek; Alena Chaikouskaya; Jacek Tabor; Elzbieta Zajac (CISIM, 2014)

Multithreshold Entropy Linear Classifier. - Wojciech Marian Czarnecki; Jacek Tabor (CoRR, 2014)

Cluster based RBF Kernel for Support Vector Machines. - Wojciech Marian Czarnecki; Jacek Tabor (CoRR, 2014)

Two ellipsoid Support Vector Machines. - Wojciech Marian Czarnecki; Jacek Tabor (Expert Syst. Appl., 2014)

Cross-entropy clustering. - Jacek Tabor; Przemyslaw Spurek (Pattern Recognit., 2014)

Online Extreme Entropy Machines for Streams Classification and Active Learning. - Wojciech Marian Czarnecki; Jacek Tabor (CORES, 2015)

Detection of Elongated Structures with Hierarchical Active Partitions and CEC-Based Image Representation. - Arkadiusz Tomczyk; Przemyslaw Spurek; Michal Podgórski; Krzysztof Misztal; Jacek Tabor (CORES, 2015)

Spherical wards clustering and generalized Voronoi diagrams. - Marek Smieja; Jacek Tabor (DSAA, 2015)

Cross-Entropy Clustering Approach to One-Class Classification. - Przemyslaw Spurek; Mateusz Wójcik; Jacek Tabor (ICAISC (1), 2015)

Maximum Entropy Linear Manifold for Learning Discriminative Low-Dimensional Representation. - Wojciech Marian Czarnecki; Rafal Józefowicz; Jacek Tabor (ECML/PKDD (1), 2015)

Introduction to Cross-Entropy Clustering The R Package CEC. - Jacek Tabor; Przemyslaw Spurek; Konrad Kamieniecki; Marek Smieja; Krzysztof Misztal (CoRR, 2015)

Entropy Approximation in Lossy Source Coding Problem. - Marek Smieja; Jacek Tabor (Entropy, 2015)

Multithreshold Entropy Linear Classifier: Theory and applications. - Wojciech Marian Czarnecki; Jacek Tabor (Expert Syst. Appl., 2015)

Optimal Ellipse Based Algorithm as an Approximate and Robust Solution of Minimum Volume Covering Ellipse Problem. - Krzysztof Misztal; Jacek Tabor; Jakub Hyla (CISIM, 2016)

Fast Entropy Clustering of sparse high dimensional binary data. - Marek Smieja; Szymon Nakoneczny; Jacek Tabor (IJCNN, 2016)

Incomplete data representation for SVM classification. - Lukasz Struski; Marek Smieja; Jacek Tabor (CoRR, 2016)

Ellipticity and Circularity Measuring via Kullback-Leibler Divergence. - Krzysztof Misztal; Jacek Tabor (J. Math. Imaging Vis., 2016)

Semi-supervised model-based clustering with controlled clusters leakage. - Marek Smieja; Lukasz Struski; Jacek Tabor (Expert Syst. Appl., 2017)

Active function Cross-Entropy Clustering. - Przemyslaw Spurek; Jacek Tabor; Krzysztof Byrski (Expert Syst. Appl., 2017)

R Package CEC. - Przemyslaw Spurek; Konrad Kamieniecki; Jacek Tabor; Krzysztof Misztal; Marek Smieja (Neurocomputing, 2017)

Extreme entropy machines: robust information theoretic classification. - Wojciech Marian Czarnecki; Jacek Tabor (Pattern Anal. Appl., 2017)

ICA based on asymmetry. - Przemyslaw Spurek; Jacek Tabor; Przemyslaw Rola; M. Ociepka (Pattern Recognit., 2017)

Processing of missing data by neural networks. - Marek Smieja; Lukasz Struski; Jacek Tabor; Bartosz Zielinski 001; Przemyslaw Spurek (NeurIPS, 2018)

Cascade context encoder for improved inpainting. - Bartosz Zielinski 001; Lukasz Struski; Marek Smieja; Jacek Tabor (CoRR, 2018)

Cramer-Wold AutoEncoder. - Jacek Tabor; Szymon Knop; Przemyslaw Spurek; Igor T. Podolak; Marcin Mazur; Stanislaw Jastrzebski (CoRR, 2018)

Deep processing of structured data. - Lukasz Maziarka; Marek Smieja; Aleksandra Nowak 001; Jacek Tabor; Lukasz Struski; Przemyslaw Spurek (CoRR, 2018)

Lossy compression approach to subspace clustering. - Lukasz Struski; Jacek Tabor; Przemyslaw Spurek (Inf. Sci., 2018)

Semi-supervised discriminative clustering with graph regularization. - Marek Smieja; Oleksandr Myronov; Jacek Tabor (Knowl. Based Syst., 2018)

Fast independent component analysis algorithm with a simple closed-form solution. - Przemyslaw Spurek; Jacek Tabor; Lukasz Struski; Marek Smieja (Knowl. Based Syst., 2018)

Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function. - Wojciech Tarnowski; Piotr Warchol; Stanislaw Jastrzebski; Jacek Tabor; Maciej A. Nowak (AISTATS, 2019)

Hypernetwork Functional Image Representation. - Sylwester Klocek; Lukasz Maziarka; Maciej Wolczyk; Jacek Tabor; Jakub Nowak; Marek Smieja (ICANN (Workshop), 2019)

Set Aggregation Network as a Trainable Pooling Layer. - Lukasz Maziarka; Marek Smieja; Aleksandra Nowak 001; Jacek Tabor; Lukasz Struski; Przemyslaw Spurek (ICONIP (2), 2019)

Sliced generative models. - Szymon Knop; Marcin Mazur; Jacek Tabor; Igor T. Podolak; Przemyslaw Spurek (CoRR, 2019)

LOSSGRAD: automatic learning rate in gradient descent. - Bartosz Wójcik; Lukasz Maziarka; Jacek Tabor (CoRR, 2019)

Multi-task hypernetworks. - Sylwester Klocek; Lukasz Maziarka; Maciej Wolczyk; Jacek Tabor; Marek Smieja; Jakub Nowak (CoRR, 2019)

Interpolation in generative models. - Lukasz Struski; Jacek Tabor; Igor T. Podolak; Aleksandra Nowak 001 (CoRR, 2019)

One-element Batch Training by Moving Window. - Przemyslaw Spurek; Szymon Knop; Jacek Tabor; Igor T. Podolak; Bartosz Wójcik (CoRR, 2019)

Independent Component Analysis based on multiple data-weighting. - Andrzej Bedychaj; Przemyslaw Spurek; Lukasz Struski; Jacek Tabor (CoRR, 2019)

SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder. - Marek Smieja; Maciej Wolczyk; Jacek Tabor; Bernhard C. Geiger (CoRR, 2019)

Geometric Graph Convolutional Neural Networks. - Przemyslaw Spurek; Tomasz Danel; Jacek Tabor; Marek Smieja; Lukasz Struski; Agnieszka Slowik; Lukasz Maziarka (CoRR, 2019)

Biologically-Inspired Spatial Neural Networks. - Maciej Wolczyk; Jacek Tabor; Marek Smieja; Szymon Maszke (CoRR, 2019)

Efficient mixture model for clustering of sparse high dimensional binary data. - Marek Smieja; Krzysztof Hajto; Jacek Tabor (Data Min. Knowl. Discov., 2019)

Development of New Methods Needs Proper Evaluation - Benchmarking Sets for Machine Learning Experiments for Class A GPCRs. - Damian Lesniak; Sabina Podlewska; Stanislaw Jastrzebski; Igor Sieradzki; Andrzej J. Bojarski; Jacek Tabor (J. Chem. Inf. Model., 2019)

Generalized RBF kernel for incomplete data. - Marek Smieja; Lukasz Struski; Jacek Tabor; Mateusz Marzec (Knowl. Based Syst., 2019)

SVM with a neutral class. - Marek Smieja; Jacek Tabor; Przemyslaw Spurek (Pattern Anal. Appl., 2019)

Online updating of active function cross-entropy clustering. - Przemyslaw Spurek; Krzysztof Byrski; Jacek Tabor (Pattern Anal. Appl., 2019)

Projected memory clustering. - Lukasz Struski; Przemyslaw Spurek; Jacek Tabor; Marek Smieja (Pattern Recognit. Lett., 2019)

Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. - Pawel Morawiecki; Przemyslaw Spurek; Marek Smieja; Jacek Tabor (ESANN, 2020)

The Break-Even Point on Optimization Trajectories of Deep Neural Networks. - Stanislaw Jastrzebski; Maciej Szymczak; Stanislav Fort; Devansh Arpit; Jacek Tabor; Kyunghyun Cho; Krzysztof J. Geras (ICLR, 2020)

Hypernetwork approach to generating point clouds. - Przemyslaw Spurek; Sebastian Winczowski; Jacek Tabor; Maciej Zamorski; Maciej Zieba; Tomasz Trzcinski (ICML, 2020)

Spatial Graph Convolutional Networks. - Tomasz Danel; Przemyslaw Spurek; Jacek Tabor; Marek Smieja; Lukasz Struski; Agnieszka Slowik; Lukasz Maziarka (ICONIP (5), 2020)

Non-linear ICA Based on Cramer-Wold Metric. - Przemyslaw Spurek; Aleksandra Nowak 001; Jacek Tabor; Lukasz Maziarka; Stanislaw Jastrzebski (ICONIP (3), 2020)

Finding the Optimal Network Depth in Classification Tasks. - Bartosz Wójcik; Maciej Wolczyk; Klaudia Balazy; Jacek Tabor (ECML/PKDD (3), 2020)

Pointed Subspace Approach to Incomplete Data. - Lukasz Struski; Marek Smieja; Jacek Tabor (J. Classif., 2020)

WICA: nonlinear weighted ICA. - Andrzej Bedychaj; Przemyslaw Spurek; Aleksandra Nowak 001; Jacek Tabor (CoRR, 2020)

Molecule Attention Transformer. - Lukasz Maziarka; Tomasz Danel; Slawomir Mucha; Krzysztof Rataj; Jacek Tabor; Stanislaw Jastrzebski (CoRR, 2020)

Kernel Self-Attention in Deep Multiple Instance Learning. - Dawid Rymarczyk; Jacek Tabor; Bartosz Zielinski 001 (CoRR, 2020)

HyperFlow: Representing 3D Objects as Surfaces. - Przemyslaw Spurek; Maciej Zieba; Jacek Tabor; Tomasz Trzcinski (CoRR, 2020)

Flow-based anomaly detection. - Lukasz Maziarka; Marek Smieja; Marcin Sendera; Lukasz Struski; Jacek Tabor; Przemyslaw Spurek (CoRR, 2020)

ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery. - Dawid Rymarczyk; Lukasz Struski; Jacek Tabor; Bartosz Zielinski 001 (CoRR, 2020)

Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening. - Stanislaw Jastrzebski; Maciej Szymczak; Agnieszka Pocha; Stefan Mordalski; Jacek Tabor; Andrzej J. Bojarski; Sabina Podlewska (J. Chem. Inf. Model., 2020)

Cramer-Wold Auto-Encoder. - Szymon Knop; Przemyslaw Spurek; Jacek Tabor; Igor T. Podolak; Marcin Mazur; Stanislaw Jastrzebski (J. Mach. Learn. Res., 2020)

Adversarial Examples Detection and Analysis with Layer-wise Autoencoders. - Bartosz Wójcik; Pawel Morawiecki; Marek Smieja; Tomasz Krzyzek; Przemyslaw Spurek; Jacek Tabor (ICTAI, 2021)

Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. - Agnieszka Pocha; Tomasz Danel; Sabina Podlewska; Jacek Tabor; Lukasz Maziarka (IJCNN, 2021)

ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification. - Dawid Rymarczyk; Lukasz Struski; Jacek Tabor; Bartosz Zielinski 001 (KDD, 2021)

Non-Gaussian Gaussian Processes for Few-Shot Regression. - Marcin Sendera; Jacek Tabor; Aleksandra Nowak 001; Andrzej Bedychaj; Massimiliano Patacchiola; Tomasz Trzcinski; Przemyslaw Spurek; Maciej Zieba (NeurIPS, 2021)

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. - Maciej Wolczyk; Bartosz Wójcik; Klaudia Balazy; Igor T. Podolak; Jacek Tabor; Marek Smieja; Tomasz Trzcinski (NeurIPS, 2021)

Direction is what you need: Improving Word Embedding Compression in Large Language Models. - Klaudia Balazy; Mohammadreza Banaei; Rémi Lebret; Jacek Tabor; Karl Aberer (RepL4NLP@ACL-IJCNLP, 2021)

Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning. - Dawid Rymarczyk; Adriana Borowa; Jacek Tabor; Bartosz Zielinski 001 (WACV, 2021)

SONG: Self-Organizing Neural Graphs. - Lukasz Struski; Tomasz Danel; Marek Smieja; Jacek Tabor; Bartosz Zielinski 001 (CoRR, 2021)

Flow-based SVDD for anomaly detection. - Marcin Sendera; Marek Smieja; Lukasz Maziarka; Lukasz Struski; Przemyslaw Spurek; Jacek Tabor (CoRR, 2021)

Convex hull of a fuzzy set and triangular norms. - Jakub Bielawski; Jacek Tabor (Fuzzy Sets Syst., 2021)

SeGMA: Semi-Supervised Gaussian Mixture Autoencoder. - Marek Smieja; Maciej Wolczyk; Jacek Tabor; Bernhard C. Geiger (IEEE Trans. Neural Networks Learn. Syst., 2021)

Interpretable Image Classification with Differentiable Prototypes Assignment. - Dawid Rymarczyk; Lukasz Struski; Michal Górszczak; Koryna Lewandowska; Jacek Tabor; Bartosz Zielinski 001 (ECCV (12), 2022)

Weakly-Supervised Cell Classification for Effective High Content Screening. - Adriana Borowa; Szczepan Kruczek; Jacek Tabor; Bartosz Zielinski 001 (ICCS (1), 2022)

Batch Size Reconstruction-Distribution Trade-Off In Kernel Based Generative Autoencoders. - Szymon Knop; Przemyslaw Spurek; Marcin Mazur; Jacek Tabor; Igor T. Podolak (ICIP, 2022)

LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. - Piotr Tempczyk; Rafal Michaluk; Lukasz Garncarek; Przemyslaw Spurek; Jacek Tabor; Adam Golinski (ICML, 2022)

Continual Learning with Guarantees via Weight Interval Constraints. - Maciej Wolczyk; Karol J. Piczak; Bartosz Wójcik; Lukasz Pustelnik; Pawel Morawiecki; Jacek Tabor; Tomasz Trzcinski; Przemyslaw Spurek (ICML, 2022)

Nonlinear Weighted Independent Component Analysis. - Andrzej Bedychaj; Przemyslaw Spurek; Aleksandra Nowak 001; Jacek Tabor (IPMU (2), 2022)

HyperPocket: Generative Point Cloud Completion. - Przemyslaw Spurek; Artur Kasymov; Marcin Mazur; Diana Janik; Slawomir Konrad Tadeja; Lukasz Struski; Jacek Tabor; Tomasz Trzcinski (IROS, 2022)

MisConv: Convolutional Neural Networks for Missing Data. - Marcin Przewiezlikowski; Marek Smieja; Lukasz Struski; Jacek Tabor (WACV, 2022)

SLOVA: Uncertainty estimation using single label one-vs-all classifier. - Bartosz Wójcik; Jacek Grela; Marek Smieja; Krzysztof Misztal; Jacek Tabor (Appl. Soft Comput., 2022)

HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks. - Marcin Przewiezlikowski; P. Przybysz; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (CoRR, 2022)

ProPaLL: Probabilistic Partial Label Learning. - Lukasz Struski; Jacek Tabor; Bartosz Zielinski 001 (CoRR, 2022)

Hypernetwork approach to Bayesian MAML. - Piotr Borycki; Piotr Kubacki; Marcin Przewiezlikowski; Tomasz Kusmierczyk; Jacek Tabor; Przemyslaw Spurek (CoRR, 2022)

HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks. - Filip Szatkowski; Karol J. Piczak; Przemyslaw Spurek; Jacek Tabor; Tomasz Trzcinski (CoRR, 2022)

LocoGAN - Locally convolutional GAN. - Lukasz Struski; Szymon Knop; Przemyslaw Spurek; Wiktor Daniec; Jacek Tabor (Comput. Vis. Image Underst., 2022)

Generative models with kernel distance in data space. - Szymon Knop; Marcin Mazur; Przemyslaw Spurek; Jacek Tabor; Igor T. Podolak (Neurocomputing, 2022)

OneFlow: One-Class Flow for Anomaly Detection Based on a Minimal Volume Region. - Lukasz Maziarka; Marek Smieja; Marcin Sendera; Lukasz Struski; Jacek Tabor; Przemyslaw Spurek (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

General Hypernetwork Framework for Creating 3D Point Clouds. - Przemyslaw Spurek; Maciej Zieba; Jacek Tabor; Tomasz Trzcinski (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Bounding Evidence and Estimating Log-Likelihood in VAE. - Lukasz Struski; Marcin Mazur; Pawel Batorski; Przemyslaw Spurek; Jacek Tabor (AISTATS, 2023)

ProPML: Probability Partial Multi-label Learning. - Lukasz Struski; Adam Pardyl; Jacek Tabor; Bartosz Zielinski 001 (DSAA, 2023)

Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models. - Mohammadreza Banaei; Klaudia Balazy; Artur Kasymov; Rémi Lebret; Jacek Tabor; Karl Aberer (EACL (Findings), 2023)

ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging. - Lukasz Struski; Dawid Rymarczyk; Arkadiusz Lewicki; Robert Sabiniewicz; Jacek Tabor; Bartosz Zielinski 001 (ECAI, 2023)

r-softmax: Generalized Softmax with Controllable Sparsity Rate. - Klaudia Balazy; Lukasz Struski; Marek Smieja; Jacek Tabor (ICCS (2), 2023)

Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. - Aleksandra Nowak 001; Bram Grooten; Decebal Constantin Mocanu; Jacek Tabor (NeurIPS, 2023)

ChiENN: Embracing Molecular Chirality with Graph Neural Networks. - Piotr Gainski; Michal Koziarski; Jacek Tabor; Marek Smieja (ECML/PKDD (3), 2023)

Hypernetworks Build Implicit Neural Representations of Sounds. - Filip Szatkowski; Karol J. Piczak; Przemyslaw Spurek; Jacek Tabor; Tomasz Trzcinski (ECML/PKDD (4), 2023)

Contrastive Hierarchical Clustering. - Michal Znalezniak; Przemyslaw Rola; Patryk Kaszuba; Jacek Tabor; Marek Smieja (ECML/PKDD (1), 2023)

ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. - Mikolaj Sacha; Dawid Rymarczyk; Lukasz Struski; Jacek Tabor; Bartosz Zielinski 001 (WACV, 2023)

HyperShot: Few-Shot Learning by Kernel HyperNetworks. - Marcin Sendera; Marcin Przewiezlikowski; Konrad Karanowski; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (WACV, 2023)

SONGs: Self-Organizing Neural Graphs. - Lukasz Struski; Tomasz Danel; Marek Smieja; Jacek Tabor; Bartosz Zielinski 001 (WACV, 2023)

NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering. - Wojciech Zajac; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (CoRR, 2023)

MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation. - Dominik Zimny; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (CoRR, 2023)

Augmentation-aware Self-supervised Learning with Guided Projector. - Marcin Przewiezlikowski; Mateusz Pyla; Bartosz Zielinski 001; Bartlomiej Twardowski; Jacek Tabor; Marek Smieja (CoRR, 2023)

MeVGAN: GAN-based Plugin Model for Video Generation with Applications in Colonoscopy. - Lukasz Struski; Tomasz Urbanczyk; Krzysztof Bucki; Bartlomiej Cupial; Aneta Kaczynska; Przemyslaw Spurek; Jacek Tabor (CoRR, 2023)

Gaussian Splatting with NeRF-based Color and Opacity. - Dawid Malarz; Weronika Smolak; Jacek Tabor; Slawomir Konrad Tadeja; Przemyslaw Spurek (CoRR, 2023)

The general framework for few-shot learning by kernel HyperNetworks. - Marcin Sendera; Marcin Przewiezlikowski; Jan Miksa; Mateusz Rajski; Konrad Karanowski; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (Mach. Vis. Appl., 2023)

Zero time waste in pre-trained early exit neural networks. - Bartosz Wójcik; Marcin Przewiezlikowski; Filip Szatkowski; Maciej Wolczyk; Klaudia Balazy; Bartlomiej Krzepkowski; Igor T. Podolak; Jacek Tabor; Marek Smieja; Tomasz Trzcinski (Neural Networks, 2023)

Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations. - Mikolaj Sacha; Bartosz Jura; Dawid Rymarczyk; Lukasz Struski; Jacek Tabor; Bartosz Zielinski 001 (AAAI, 2024)

RegFlow: Probabilistic Flow-Based Regression for Future Prediction. - Maciej Zieba; Marcin Przewiezlikowski; Marek Smieja; Jacek Tabor; Tomasz Trzcinski; Przemyslaw Spurek (ACIIDS (Companion 2), 2024)

NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering. - Wojciech Zajac; Joanna Waczynska; Piotr Borycki; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (ICCS (1), 2024)

Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization. - Aleksandra Nowak 001; Lukasz Gniecki; Filip Szatkowski; Jacek Tabor (ICML, 2024)

StyleAutoEncoder for Manipulating Image Attributes Using Pre-trained StyleGAN. - Andrzej Bedychaj; Jacek Tabor; Marek Smieja (PAKDD (2), 2024)

Face Identity-Aware Disentanglement in StyleGAN. - Adrian Suwala; Bartosz Wójcik; Magdalena Proszewska; Jacek Tabor; Przemyslaw Spurek; Marek Smieja (WACV, 2024)

Multiple instance learning for medical image classification based on instance importance. - Lukasz Struski; Szymon Janusz; Jacek Tabor; Michal Markiewicz; Arkadiusz Lewicki (Biomed. Signal Process. Control., 2024)

GaMeS: Mesh-Based Adapting and Modification of Gaussian Splatting. - Joanna Waczynska; Piotr Borycki; Slawomir Konrad Tadeja; Jacek Tabor; Przemyslaw Spurek (CoRR, 2024)

ImplicitDeepfake: Plausible Face-Swapping through Implicit Deepfake Generation using NeRF and Gaussian Splatting. - Georgii Stanishevskii; Jakub Steczkiewicz; Tomasz Szczepanik; Slawomir Konrad Tadeja; Jacek Tabor; Przemyslaw Spurek (CoRR, 2024)

LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters. - Klaudia Balazy; Mohammadreza Banaei; Karl Aberer; Jacek Tabor (CoRR, 2024)

Sparser, Better, Deeper, Stronger: Improving Sparse Training with Exact Orthogonal Initialization. - Aleksandra Irena Nowak; Lukasz Gniecki; Filip Szatkowski; Jacek Tabor (CoRR, 2024)

PrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification. - Magdalena Tredowicz; Lukasz Struski; Marcin Mazur; Szymon Janusz; Arkadiusz Lewicki; Jacek Tabor (CoRR, 2024)

RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets. - Piotr Gainski; Michal Koziarski; Krzysztof Maziarz; Marwin H. S. Segler; Jacek Tabor; Marek Smieja (CoRR, 2024)

InfoDisent: Explainability of Image Classification Models by Information Disentanglement. - Lukasz Struski; Jacek Tabor (CoRR, 2024)

Make Interval Bound Propagation great again. - Patryk Krukowski; Daniel Wilczak; Jacek Tabor; Anna Bielawska; Przemyslaw Spurek (CoRR, 2024)

Gaussian model for closed curves. - Krzysztof Byrski; Jacek Tabor; Przemyslaw Spurek (Expert Syst. Appl., 2024)

Augmentation-aware self-supervised learning with conditioned projector. - Marcin Przewiezlikowski; Mateusz Pyla; Bartosz Zielinski 001; Bartlomiej Twardowski; Jacek Tabor; Marek Smieja (Knowl. Based Syst., 2024)

Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models. - Lukasz Struski; Michal Sadowski; Tomasz Danel; Jacek Tabor; Igor T. Podolak (IEEE Trans. Neural Networks Learn. Syst., 2024)

Relative molecule self-attention transformer. - Lukasz Maziarka; Dawid Majchrowski; Tomasz Danel; Piotr Gainski; Jacek Tabor; Igor T. Podolak; Pawel M. Morkisz; Stanislaw Jastrzebski (J. Cheminformatics, 2024)

Hypernetwork Approach to Bayesian MAML (Student Abstract). - Piotr Borycki; Piotr Kubacki; Marcin Przewiezlikowski; Tomasz Kusmierczyk; Jacek Tabor; Przemyslaw Spurek (AAAI, 2025)

A Deeper Look into the Limitations of Early-Exit Architectures for Single and Multi-label Classification. - Klaudia Balazy; Julian J. McAuley; Jacek Tabor (ICCS (1), 2025)

FreSh: Frequency Shifting for Accelerated Neural Representation Learning. - Adam Kania; Marko Mihajlovic; Sergey Prokudin; Jacek Tabor; Przemyslaw Spurek (ICLR, 2025)

LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision. - Mateusz Pach; Koryna Lewandowska; Jacek Tabor; Bartosz Michal Zielinski; Dawid Damian Rymarczyk (ICLR, 2025)

VisTabNet: Adapting Vision Transformers for Tabular Data. - Witold Wydmanski; Ulvi Movsum-zada; Jacek Tabor; Marek Smieja (SDM, 2025)

GeoGuide: Geometric Guidance of Diffusion Models. - Mateusz Poleski; Jacek Tabor; Przemyslaw Spurek (WACV, 2025)

Gaussian Splatting with NeRF-based color and opacity. - Dawid Malarz; Weronika Smolak-Dyzewska; Jacek Tabor; Slawomir Konrad Tadeja; Przemyslaw Spurek (Comput. Vis. Image Underst., 2025)

MultiPlaneNeRF: Neural radiance field with non-trainable representation. - Dominik Zimny; Artur Kasymov; Adam Kania; Jacek Tabor; Maciej Zieba; Marcin Mazur; Przemyslaw Spurek (Expert Syst. Appl., 2025)

Diverse and feasible retrosynthesis using GFlowNets. - Piotr Gainski; Michal Koziarski; Krzysztof Maziarz; Marwin H. S. Segler; Jacek Tabor; Marek Smieja (Inf. Sci., 2025)

NegGS: Negative Gaussian Splatting. - Artur Kasymov; Bartosz Czekaj; Marcin Mazur; Jacek Tabor; Przemyslaw Spurek (Inf. Sci., 2025)

RaySplats: Ray Tracing based Gaussian Splatting. - Krzysztof Byrski; Marcin Mazur; Jacek Tabor; Tadeusz Dziarmaga; Marcin Kadziolka; Dawid Baran; Przemyslaw Spurek (CoRR, 2025)

SEMU: Singular Value Decomposition for Efficient Machine Unlearning. - Marcin Sendera; Lukasz Struski; Kamil Ksiazek; Kryspin Musiol; Jacek Tabor; Dawid Rymarczyk (CoRR, 2025)

Classifier-free Guidance with Adaptive Scaling. - Dawid Malarz; Artur Kasymov; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (CoRR, 2025)

Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA. - Patryk Marszalek; Klaudia Balazy; Jacek Tabor; Tomasz Kusmierczyk (CoRR, 2025)

LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection. - Lukasz Struski; Michal B. Bednarczyk; Igor T. Podolak; Jacek Tabor (CoRR, 2025)

FeNeC: Enhancing Continual Learning via Feature Clustering with Neighbor- or Logit-Based Classification. - Kamil Ksiazek; Hubert Jastrzebski; Bartosz Trojan; Krzysztof Pniaczek; Michal Karp; Jacek Tabor (CoRR, 2025)

CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression. - Krzysztof Byrski; Jacek Tabor; Przemyslaw Spurek; Marcin Mazur (CoRR, 2025)

ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data. - Patryk Marszalek; Tomasz Kusmierczyk; Witold Wydmanski; Jacek Tabor; Marek Smieja (CoRR, 2025)

EPIC: Explanation of Pretrained Image Classification Networks via Prototype. - Piotr Borycki; Magdalena Tredowicz; Szymon Janusz; Jacek Tabor; Przemyslaw Spurek; Arkadiusz Lewicki; Lukasz Struski (CoRR, 2025)

SIDE: Sparse Information Disentanglement for Explainable Artificial Intelligence. - Viktar Dubovik; Lukasz Struski; Jacek Tabor; Dawid Rymarczyk (CoRR, 2025)

UnGuide: Learning to Forget with LoRA-Guided Diffusion Models. - Agnieszka Polowczyk; Alicja Polowczyk; Dawid Malarz; Artur Kasymov; Marcin Mazur; Jacek Tabor; Przemyslaw Spurek (CoRR, 2025)