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

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

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

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

Subspaces Clustering Approach to Lossy Image Compression. - Przemyslaw Spurek; Marek Smieja; Krzysztof Misztal (CISIM, 2014)

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

Weighted approach to general entropy function. - Marek Smieja (IMA J. Math. Control. Inf., 2015)

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)

Constrained clustering with a complex cluster structure. - Marek Smieja; Magdalena Wiercioch (Adv. Data Anal. Classif., 2017)

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

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

Semi-supervised cross-entropy clustering with information bottleneck constraint. - Marek Smieja; Bernhard C. Geiger (Inf. Sci., 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)

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

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)

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

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)

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)

Processing of Incomplete Images by (Graph) Convolutional Neural Networks. - Tomasz Danel; Marek Smieja; Lukasz Struski; Przemyslaw Spurek; Lukasz Maziarka (ICONIP (2), 2020)

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

Estimating Conditional Density of Missing Values Using Deep Gaussian Mixture Model. - Marcin Przewiezlikowski; Marek Smieja; Lukasz Struski (ICONIP (3), 2020)

Iterative Imputation of Missing Data Using Auto-Encoder Dynamics. - Marek Smieja; Maciej Kolomycki; Lukasz Struski; Mateusz Juda; Mário A. T. Figueiredo (ICONIP (3), 2020)

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

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

A classification-based approach to semi-supervised clustering with pairwise constraints. - Marek Smieja; Lukasz Struski; Mário A. T. Figueiredo (Neural Networks, 2020)

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

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)

Semi-Supervised Clustering via Markov Chain Aggregation. - Sophie Steger; Bernhard C. Geiger; Marek Smieja (CoRR, 2021)

Pharmacoprint: A Combination of a Pharmacophore Fingerprint and Artificial Intelligence as a Tool for Computer-Aided Drug Design. - Dawid Warszycki; Lukasz Struski; Marek Smieja; Rafal Kafel; Rafal Kurczab (J. Chem. Inf. Model., 2021)

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

PluGeN: Multi-Label Conditional Generation from Pre-trained Models. - Maciej Wolczyk; Magdalena Proszewska; Lukasz Maziarka; Maciej Zieba; Patryk Wielopolski; Rafal Kurczab; Marek Smieja (AAAI, 2022)

Semi-supervised clustering via information-theoretic markov chain aggregation. - Sophie Steger; Bernhard C. Geiger; Marek Smieja (SAC, 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)

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)

HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasets. - Witold Wydmanski; Oleksii Bulenok; Marek Smieja (DSAA, 2023)

Hebbian Continual Representation Learning. - Pawel Morawiecki; Andrii Krutsylo; Maciej Wolczyk; Marek Smieja (HICSS, 2023)

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

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

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

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

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

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

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

A Deep Cut Into Split Federated Self-Supervised Learning. - Marcin Przewiezlikowski; Marcin Osial; Bartosz Zielinski 001; Marek Smieja (ECML/PKDD (2), 2024)

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

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

Beyond [cls]: Exploring the true potential of Masked Image Modeling representations. - Marcin Przewiezlikowski; Randall Balestriero; Wojciech Jasinski; Marek Smieja; Bartosz Zielinski 001 (CoRR, 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)

ADMET-PrInt: Evaluation of ADMET Properties: Prediction and Interpretation. - Ewelina Jamrozik; Marek Smieja; Sabina Podlewska (J. Chem. Inf. Model., 2024)

Multi-Label Conditional Generation From Pre-Trained Models. - Magdalena Proszewska; Maciej Wolczyk; Maciej Zieba; Patryk Wielopolski; Lukasz Maziarka; Marek Smieja (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

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

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

HyConEx: Hypernetwork classifier with counterfactual explanations. - Patryk Marszalek; Ulvi Movsum-zada; Oleksii Furman; Kamil Ksiazek; Przemyslaw Spurek; Marek Smieja (CoRR, 2025)

GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid Relaxation. - Witold Wydmanski; Marek Smieja (CoRR, 2025)

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

DiCoFlex: Model-agnostic diverse counterfactuals with flexible control. - Oleksii Furman; Ulvi Movsum-zada; Patryk Marszalek; Maciej Zieba; Marek Smieja (CoRR, 2025)