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2020 – today
- 2024
[j23]Ewelina Jamrozik, Marek Smieja, Sabina Podlewska
:
ADMET-PrInt: Evaluation of ADMET Properties: Prediction and Interpretation. J. Chem. Inf. Model. 64(5): 1425-1432 (2024)- [j22]Marcin Przewiezlikowski, Mateusz Pyla, Bartosz Zielinski, Bartlomiej Twardowski, Jacek Tabor, Marek Smieja:
Augmentation-aware self-supervised learning with conditioned projector. Knowl. Based Syst. 305: 112572 (2024) - [j21]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) - [c27]Maciej Zieba, Marcin Przewiezlikowski, Marek Smieja, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
RegFlow: Probabilistic Flow-Based Regression for Future Prediction. ACIIDS (Companion 2) 2024: 267-279 - [c26]Andrzej Bedychaj, Jacek Tabor, Marek Smieja:
StyleAutoEncoder for Manipulating Image Attributes Using Pre-trained StyleGAN. PAKDD (2) 2024: 118-130 - [c25]Marcin Przewiezlikowski, Marcin Osial, Bartosz Zielinski, Marek Smieja:
A Deep Cut Into Split Federated Self-Supervised Learning. ECML/PKDD (2) 2024: 444-459 - [c24]Adrian Suwala, Bartosz Wójcik, Magdalena Proszewska, Jacek Tabor, Przemyslaw Spurek, Marek Smieja:
Face Identity-Aware Disentanglement in StyleGAN. WACV 2024: 5210-5219 - [i42]Marcin Przewiezlikowski, Marcin Osial, Bartosz Zielinski, Marek Smieja:
A deep cut into Split Federated Self-supervised Learning. CoRR abs/2406.08267 (2024) - [i41]Piotr Gainski, Michal Koziarski, Krzysztof Maziarz, Marwin H. S. Segler, Jacek Tabor, Marek Smieja:
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets. CoRR abs/2406.18739 (2024) - 2023
- [j20]Bartosz Wójcik, Marcin Przewiezlikowski, Filip Szatkowski, Maciej Wolczyk, Klaudia Balazy, Bartlomiej Krzepkowski, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero time waste in pre-trained early exit neural networks. Neural Networks 168: 580-601 (2023) - [c23]Witold Wydmanski, Oleksii Bulenok, Marek Smieja:
HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasets. DSAA 2023: 1-9 - [c22]Pawel Morawiecki, Andrii Krutsylo, Maciej Wolczyk, Marek Smieja:
Hebbian Continual Representation Learning. HICSS 2023: 1259-1268 - [c21]Klaudia Balazy, Lukasz Struski, Marek Smieja, Jacek Tabor:
r-softmax: Generalized Softmax with Controllable Sparsity Rate. ICCS (2) 2023: 137-145 - [c20]Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja:
ChiENN: Embracing Molecular Chirality with Graph Neural Networks. ECML/PKDD (3) 2023: 36-52 - [c19]Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja:
Contrastive Hierarchical Clustering. ECML/PKDD (1) 2023: 627-643 - [c18]Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski:
SONGs: Self-Organizing Neural Graphs. WACV 2023: 3837-3846 - [i40]Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja:
Contrastive Hierarchical Clustering. CoRR abs/2303.03389 (2023) - [i39]Witold Wydmanski, Oleksii Bulenok, Marek Smieja:
HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasets. CoRR abs/2304.03543 (2023) - [i38]Klaudia Balazy, Lukasz Struski, Marek Smieja, Jacek Tabor:
r-softmax: Generalized Softmax with Controllable Sparsity Rate. CoRR abs/2304.05243 (2023) - [i37]Marcin Przewiezlikowski, Mateusz Pyla, Bartosz Zielinski, Bartlomiej Twardowski, Jacek Tabor, Marek Smieja:
Augmentation-aware Self-supervised Learning with Guided Projector. CoRR abs/2306.06082 (2023) - [i36]Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja:
ChiENN: Embracing Molecular Chirality with Graph Neural Networks. CoRR abs/2307.02198 (2023) - [i35]Adrian Suwala, Bartosz Wójcik, Magdalena Proszewska, Jacek Tabor, Przemyslaw Spurek, Marek Smieja:
Face Identity-Aware Disentanglement in StyleGAN. CoRR abs/2309.12033 (2023) - 2022
- [j19]Bartosz Wójcik, Jacek Grela, Marek Smieja, Krzysztof Misztal, Jacek Tabor:
SLOVA: Uncertainty estimation using single label one-vs-all classifier. Appl. Soft Comput. 126: 109219 (2022) - [j18]Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek:
OneFlow: One-Class Flow for Anomaly Detection Based on a Minimal Volume Region. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 8508-8519 (2022) - [c17]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 - [c16]Sophie Steger, Bernhard C. Geiger, Marek Smieja:
Semi-supervised clustering via information-theoretic markov chain aggregation. SAC 2022: 1136-1139 - [c15]Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski, Jacek Tabor:
MisConv: Convolutional Neural Networks for Missing Data. WACV 2022: 2917-2926 - [i34]Bartosz Wójcik, Jacek Grela, Marek Smieja, Krzysztof Misztal, Jacek Tabor:
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier. CoRR abs/2206.13923 (2022) - [i33]Pawel Morawiecki, Andrii Krutsylo, Maciej Wolczyk, Marek Smieja:
Hebbian Continual Representation Learning. CoRR abs/2207.04874 (2022) - 2021
- [j17]Dawid Warszycki, Lukasz Struski, Marek Smieja, Rafal Kafel, Rafal Kurczab:
Pharmacoprint: A Combination of a Pharmacophore Fingerprint and Artificial Intelligence as a Tool for Computer-Aided Drug Design. J. Chem. Inf. Model. 61(10): 5054-5065 (2021) - [j16]Marek Smieja, Maciej Wolczyk, Jacek Tabor, Bernhard C. Geiger:
SeGMA: Semi-Supervised Gaussian Mixture Autoencoder. IEEE Trans. Neural Networks Learn. Syst. 32(9): 3930-3941 (2021) - [c14]Bartosz Wójcik, Pawel Morawiecki, Marek Smieja, Tomasz Krzyzek, Przemyslaw Spurek, Jacek Tabor:
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders. ICTAI 2021: 1322-1326 - [c13]Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. NeurIPS 2021: 2516-2528 - [i32]Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. CoRR abs/2106.05409 (2021) - [i31]Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski:
SONG: Self-Organizing Neural Graphs. CoRR abs/2107.13214 (2021) - [i30]Marcin Sendera, Marek Smieja, Lukasz Maziarka, Lukasz Struski, Przemyslaw Spurek, Jacek Tabor:
Flow-based SVDD for anomaly detection. CoRR abs/2108.04907 (2021) - [i29]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) - [i28]Dawid Warszycki, Lukasz Struski, Marek Smieja, Rafal Kafel, Rafal Kurczab:
Pharmacoprint - a combination of pharmacophore fingerprint and artificial intelligence as a tool for computer-aided drug design. CoRR abs/2110.01339 (2021) - [i27]Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski, Jacek Tabor:
MisConv: Convolutional Neural Networks for Missing Data. CoRR abs/2110.14010 (2021) - [i26]Sophie Steger, Bernhard C. Geiger, Marek Smieja:
Semi-Supervised Clustering via Markov Chain Aggregation. CoRR abs/2112.09397 (2021) - 2020
- [j15]Lukasz Struski, Marek Smieja, Jacek Tabor:
Pointed Subspace Approach to Incomplete Data. J. Classif. 37(1): 42-57 (2020) - [j14]Marek Smieja, Lukasz Struski, Mário A. T. Figueiredo:
A classification-based approach to semi-supervised clustering with pairwise constraints. Neural Networks 127: 193-203 (2020) - [c12]Pawel Morawiecki, Przemyslaw Spurek, Marek Smieja, Jacek Tabor:
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. ESANN 2020: 55-60 - [c11]Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski:
Estimating Conditional Density of Missing Values Using Deep Gaussian Mixture Model. ICONIP (3) 2020: 220-231 - [c10]Marek Smieja, Maciej Kolomycki, Lukasz Struski, Mateusz Juda, Mário A. T. Figueiredo:
Iterative Imputation of Missing Data Using Auto-Encoder Dynamics. ICONIP (3) 2020: 258-269 - [c9]Tomasz Danel, Marek Smieja, Lukasz Struski, Przemyslaw Spurek, Lukasz Maziarka:
Processing of Incomplete Images by (Graph) Convolutional Neural Networks. ICONIP (2) 2020: 512-523 - [c8]Tomasz Danel, Przemyslaw Spurek, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka:
Spatial Graph Convolutional Networks. ICONIP (5) 2020: 668-675 - [i25]Marek Smieja, Lukasz Struski, Mário A. T. Figueiredo:
A Classification-Based Approach to Semi-Supervised Clustering with Pairwise Constraints. CoRR abs/2001.06720 (2020) - [i24]Bartosz Wójcik, Pawel Morawiecki, Marek Smieja, Tomasz Krzyzek, Przemyslaw Spurek, Jacek Tabor:
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders. CoRR abs/2006.10013 (2020) - [i23]Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski:
Estimating conditional density of missing values using deep Gaussian mixture model. CoRR abs/2010.02183 (2020) - [i22]Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek:
Flow-based anomaly detection. CoRR abs/2010.03002 (2020) - [i21]Tomasz Danel, Marek Smieja, Lukasz Struski, Przemyslaw Spurek, Lukasz Maziarka:
Processing of incomplete images by (graph) convolutional neural networks. CoRR abs/2010.13914 (2020) - [i20]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
- [j13]Marek Smieja, Krzysztof Hajto, Jacek Tabor:
Efficient mixture model for clustering of sparse high dimensional binary data. Data Min. Knowl. Discov. 33(6): 1583-1624 (2019) - [j12]Marek Smieja, Lukasz Struski, Jacek Tabor, Mateusz Marzec:
Generalized RBF kernel for incomplete data. Knowl. Based Syst. 173: 150-162 (2019) - [j11]Marek Smieja, Jacek Tabor, Przemyslaw Spurek:
SVM with a neutral class. Pattern Anal. Appl. 22(2): 573-582 (2019) - [j10]Lukasz Struski, Przemyslaw Spurek, Jacek Tabor, Marek Smieja:
Projected memory clustering. Pattern Recognit. Lett. 123: 9-15 (2019) - [c7]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Jakub Nowak, Marek Smieja:
Hypernetwork Functional Image Representation. ICANN (Workshop) 2019: 496-510 - [c6]Lukasz Maziarka, Marek Smieja, Aleksandra Nowak, Jacek Tabor, Lukasz Struski, Przemyslaw Spurek:
Set Aggregation Network as a Trainable Pooling Layer. ICONIP (2) 2019: 419-431 - [i19]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Marek Smieja, Jakub Nowak:
Multi-task hypernetworks. CoRR abs/1902.10404 (2019) - [i18]Pawel Morawiecki, Przemyslaw Spurek, Marek Smieja, Jacek Tabor:
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. CoRR abs/1906.00628 (2019) - [i17]Marek Smieja, Maciej Wolczyk, Jacek Tabor, Bernhard C. Geiger:
SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder. CoRR abs/1906.09333 (2019) - [i16]Przemyslaw Spurek, Tomasz Danel, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka:
Geometric Graph Convolutional Neural Networks. CoRR abs/1909.05310 (2019) - [i15]Maciej Wolczyk, Jacek Tabor, Marek Smieja, Szymon Maszke:
Biologically-Inspired Spatial Neural Networks. CoRR abs/1910.02776 (2019) - 2018
- [j9]Marek Smieja, Oleksandr Myronov, Jacek Tabor:
Semi-supervised discriminative clustering with graph regularization. Knowl. Based Syst. 151: 24-36 (2018) - [j8]Przemyslaw Spurek, Jacek Tabor, Lukasz Struski, Marek Smieja:
Fast independent component analysis algorithm with a simple closed-form solution. Knowl. Based Syst. 161: 26-34 (2018) - [c5]Marek Smieja, Lukasz Struski, Jacek Tabor, Bartosz Zielinski, Przemyslaw Spurek:
Processing of missing data by neural networks. NeurIPS 2018: 2724-2734 - [i14]Bartosz Zielinski, Lukasz Struski, Marek Smieja, Jacek Tabor:
Cascade context encoder for improved inpainting. CoRR abs/1803.04033 (2018) - [i13]Marek Smieja, Lukasz Struski, Jacek Tabor, Bartosz Zielinski, Przemyslaw Spurek:
Processing of missing data by neural networks. CoRR abs/1805.07405 (2018) - [i12]Lukasz Maziarka, Marek Smieja, Aleksandra Nowak, Jacek Tabor, Lukasz Struski, Przemyslaw Spurek:
Deep processing of structured data. CoRR abs/1810.01868 (2018) - 2017
- [j7]Marek Smieja, Magdalena Wiercioch:
Constrained clustering with a complex cluster structure. Adv. Data Anal. Classif. 11(3): 493-518 (2017) - [j6]Marek Smieja, Lukasz Struski, Jacek Tabor:
Semi-supervised model-based clustering with controlled clusters leakage. Expert Syst. Appl. 85: 146-157 (2017) - [j5]Przemyslaw Spurek, Konrad Kamieniecki, Jacek Tabor, Krzysztof Misztal, Marek Smieja:
R Package CEC. Neurocomputing 237: 410-413 (2017) - [j4]Marek Smieja, Bernhard C. Geiger:
Semi-supervised cross-entropy clustering with information bottleneck constraint. Inf. Sci. 421: 254-271 (2017) - [i11]Lukasz Struski, Marek Smieja, Jacek Tabor:
Pointed subspace approach to incomplete data. CoRR abs/1705.00840 (2017) - [i10]Marek Smieja, Bernhard C. Geiger:
Semi-supervised cross-entropy clustering with information bottleneck constraint. CoRR abs/1705.01601 (2017) - [i9]Marek Smieja, Lukasz Struski, Jacek Tabor:
Semi-supervised model-based clustering with controlled clusters leakage. CoRR abs/1705.01877 (2017) - [i8]Marek Smieja, Jacek Tabor:
Spherical Wards clustering and generalized Voronoi diagrams. CoRR abs/1705.02232 (2017) - [i7]Marek Smieja, Krzysztof Hajto, Jacek Tabor:
Efficient mixture model for clustering of sparse high dimensional binary data. CoRR abs/1707.03157 (2017) - 2016
- [c4]Marek Smieja, Szymon Nakoneczny, Jacek Tabor:
Fast Entropy Clustering of sparse high dimensional binary data. IJCNN 2016: 2397-2404 - [i6]Lukasz Struski, Marek Smieja, Jacek Tabor:
Incomplete data representation for SVM classification. CoRR abs/1612.01480 (2016) - 2015
- [j3]Marek Smieja, Jacek Tabor:
Entropy Approximation in Lossy Source Coding Problem. Entropy 17(5): 3400-3418 (2015) - [j2]Marek Smieja:
Weighted approach to general entropy function. IMA J. Math. Control. Inf. 32(2): 329-341 (2015) - [c3]Marek Smieja, Jacek Tabor:
Spherical wards clustering and generalized Voronoi diagrams. DSAA 2015: 1-10 - [i5]Jacek Tabor, Przemyslaw Spurek, Konrad Kamieniecki, Marek Smieja, Krzysztof Misztal:
Introduction to Cross-Entropy Clustering The R Package CEC. CoRR abs/1508.04559 (2015) - 2014
- [c2]Przemyslaw Spurek, Marek Smieja, Krzysztof Misztal:
Subspaces Clustering Approach to Lossy Image Compression. CISIM 2014: 571-579 - 2013
- [c1]Marek Smieja, Jacek Tabor:
Image Segmentation with Use of Cross-Entropy Clustering. CORES 2013: 403-409 - [i4]Marek Smieja:
Weighted Approach to General Entropy Function. CoRR abs/1305.3040 (2013) - 2012
- [j1]Marek Smieja, Jacek Tabor:
Entropy of the Mixture of Sources and Entropy Dimension. IEEE Trans. Inf. Theory 58(5): 2719-2728 (2012) - [i3]Marek Smieja, Jacek Tabor:
Weighted Approach to Rényi Entropy. CoRR abs/1204.0075 (2012) - [i2]Marek Smieja, Jacek Tabor:
Partition Reduction for Lossy Data Compression Problem. CoRR abs/1204.0078 (2012) - 2011
- [i1]Marek Smieja, Jacek Tabor:
Entropy of the Mixture of Sources and Entropy Dimension. CoRR abs/1110.6027 (2011)
Coauthor Index
[j22] [c27] [c26] [c24] [i41] [j20] [c21] [c20] [c19] [c18] [i40] [i38] [i37] [i36] [i35] [j19] [j18] [c15] [i34] [j16] [c14] [c13] [i32] [i31] [i30] [i27] [j15] [c12] [c8] [i24] [i22] [i20] [j13] [j12] [j11] [j10] [c7] [c6] [i19] [i18] [i17] [i16] [i15] [j9] [j8] [c5] [i14] [i13] [i12] [j6] [j5] [i11] [i9] [i8] [i7] [c4] [i6] [j3] [c3] [i5] [c1] [j1] [i3] [i2] [i1]
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