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2020 – today
- 2023
[j34]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)- [c48]Lukasz Struski, Marcin Mazur, Pawel Batorski, Przemyslaw Spurek, Jacek Tabor:
Bounding Evidence and Estimating Log-Likelihood in VAE. AISTATS 2023: 5036-5051 - [c47]Mohammadreza Banaei, Klaudia Balazy, Artur Kasymov, Rémi Lebret, Jacek Tabor, Karl Aberer:
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models. EACL (Findings) 2023: 1743-1760 - [c46]Klaudia Balazy, Lukasz Struski, Marek Smieja, Jacek Tabor:
r-softmax: Generalized Softmax with Controllable Sparsity Rate. ICCS (2) 2023: 137-145 - [c45]Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja:
ChiENN: Embracing Molecular Chirality with Graph Neural Networks. ECML/PKDD (3) 2023: 36-52 - [c44]Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja:
Contrastive Hierarchical Clustering. ECML/PKDD (1) 2023: 627-643 - [c43]Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski:
Hypernetworks Build Implicit Neural Representations of Sounds. ECML/PKDD (4) 2023: 661-676 - [c42]Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. WACV 2023: 1481-1492 - [c41]Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek:
HyperShot: Few-Shot Learning by Kernel HyperNetworks. WACV 2023: 2468-2477 - [c40]Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski:
SONGs: Self-Organizing Neural Graphs. WACV 2023: 3837-3846 - [i80]Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. CoRR abs/2301.12276 (2023) - [i79]Mohammadreza Banaei, Klaudia Balazy, Artur Kasymov, Rémi Lebret, Jacek Tabor, Karl Aberer:
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models. CoRR abs/2302.04045 (2023) - [i78]Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski:
Hypernetworks build Implicit Neural Representations of Sounds. CoRR abs/2302.04959 (2023) - [i77]Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja:
Contrastive Hierarchical Clustering. CoRR abs/2303.03389 (2023) - [i76]Wojciech Zajac, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering. CoRR abs/2303.06226 (2023) - [i75]Krzysztof Byrski, Przemyslaw Spurek, Jacek Tabor:
Gaussian model for closed curves. CoRR abs/2304.01367 (2023) - [i74]Klaudia Balazy, Lukasz Struski, Marek Smieja, Jacek Tabor:
r-softmax: Generalized Softmax with Controllable Sparsity Rate. CoRR abs/2304.05243 (2023) - [i73]Dominik Zimny, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation. CoRR abs/2305.10579 (2023) - [i72]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) - [i71]Lukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor, Bartosz Zielinski:
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging. CoRR abs/2306.10535 (2023) - [i70]Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor:
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. CoRR abs/2306.12230 (2023) - [i69]Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja:
ChiENN: Embracing Molecular Chirality with Graph Neural Networks. CoRR abs/2307.02198 (2023) - [i68]Mikolaj Sacha, Bartosz Jura, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations. CoRR abs/2308.08162 (2023) - [i67]Adrian Suwala, Bartosz Wójcik, Magdalena Proszewska, Jacek Tabor, Przemyslaw Spurek, Marek Smieja:
Face Identity-Aware Disentanglement in StyleGAN. CoRR abs/2309.12033 (2023) - 2022
- [j33]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) - [j32]Lukasz Struski, Szymon Knop, Przemyslaw Spurek, Wiktor Daniec, Jacek Tabor:
LocoGAN - Locally convolutional GAN. Comput. Vis. Image Underst. 221: 103462 (2022) - [j31]Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak:
Generative models with kernel distance in data space. Neurocomputing 487: 119-129 (2022) - [j30]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) - [j29]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) - [c39]Dawid Rymarczyk, Lukasz Struski, Michal Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski:
Interpretable Image Classification with Differentiable Prototypes Assignment. ECCV (12) 2022: 351-368 - [c38]Adriana Borowa, Szczepan Kruczek, Jacek Tabor, Bartosz Zielinski:
Weakly-Supervised Cell Classification for Effective High Content Screening. ICCS (1) 2022: 318-330 - [c37]Szymon Knop, Przemyslaw Spurek, Marcin Mazur, Jacek Tabor, Igor T. Podolak:
Batch Size Reconstruction-Distribution Trade-Off In Kernel Based Generative Autoencoders. ICIP 2022: 3728-3732 - [c36]Piotr Tempczyk, Rafal Michaluk, Lukasz Garncarek, Przemyslaw Spurek, Jacek Tabor, Adam Golinski:
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. ICML 2022: 21205-21231 - [c35]Maciej Wolczyk, Karol J. Piczak, Bartosz Wójcik, Lukasz Pustelnik, Pawel Morawiecki, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
Continual Learning with Guarantees via Weight Interval Constraints. ICML 2022: 23897-23911 - [c34]Andrzej Bedychaj, Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor:
Nonlinear Weighted Independent Component Analysis. IPMU (2) 2022: 3-16 - [c33]Przemyslaw Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Slawomir Konrad Tadeja, Lukasz Struski, Jacek Tabor, Tomasz Trzcinski:
HyperPocket: Generative Point Cloud Completion. IROS 2022: 6848-6853 - [c32]Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski, Jacek Tabor:
MisConv: Convolutional Neural Networks for Missing Data. WACV 2022: 2917-2926 - [i66]Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek:
HyperShot: Few-Shot Learning by Kernel HyperNetworks. CoRR abs/2203.11378 (2022) - [i65]Marcin Przewiezlikowski, P. Przybysz, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek:
HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks. CoRR abs/2205.15745 (2022) - [i64]Maciej Wolczyk, Karol J. Piczak, Bartosz Wójcik, Lukasz Pustelnik, Pawel Morawiecki, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
Continual Learning with Guarantees via Weight Interval Constraints. CoRR abs/2206.07996 (2022) - [i63]Lukasz Struski, Marcin Mazur, Pawel Batorski, Przemyslaw Spurek, Jacek Tabor:
Bounding Evidence and Estimating Log-Likelihood in VAE. CoRR abs/2206.09453 (2022) - [i62]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) - [i61]Piotr Tempczyk, Rafal Michaluk, Lukasz Garncarek, Przemyslaw Spurek, Jacek Tabor, Adam Golinski:
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. CoRR abs/2206.14882 (2022) - [i60]Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProPaLL: Probabilistic Partial Label Learning. CoRR abs/2208.09931 (2022) - [i59]Piotr Borycki, Piotr Kubacki, Marcin Przewiezlikowski, Tomasz Kusmierczyk, Jacek Tabor, Przemyslaw Spurek:
Hypernetwork approach to Bayesian MAML. CoRR abs/2210.02796 (2022) - [i58]Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski:
HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks. CoRR abs/2211.01839 (2022) - 2021
- [j28]Jakub Bielawski, Jacek Tabor:
Convex hull of a fuzzy set and triangular norms. Fuzzy Sets Syst. 417: 93-109 (2021) - [j27]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) - [c31]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 - [c30]Agnieszka Pocha, Tomasz Danel, Sabina Podlewska, Jacek Tabor, Lukasz Maziarka:
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. IJCNN 2021: 1-8 - [c29]Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification. KDD 2021: 1420-1430 - [c28]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 - [c27]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 - [c26]Klaudia Balazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor, Karl Aberer:
Direction is what you need: Improving Word Embedding Compression in Large Language Models. RepL4NLP@ACL-IJCNLP 2021: 322-330 - [c25]Dawid Rymarczyk, Adriana Borowa, Jacek Tabor, Bartosz Zielinski:
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning. WACV 2021: 1720-1729 - [i57]Przemyslaw Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Slawomir Konrad Tadeja, Lukasz Struski, Jacek Tabor, Tomasz Trzcinski:
HyperPocket: Generative Point Cloud Completion. CoRR abs/2102.05973 (2021) - [i56]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) - [i55]Klaudia Balazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor, Karl Aberer:
Direction is what you need: Improving Word Embedding Compression in Large Language Models. CoRR abs/2106.08181 (2021) - [i54]Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski:
SONG: Self-Organizing Neural Graphs. CoRR abs/2107.13214 (2021) - [i53]Marcin Sendera, Marek Smieja, Lukasz Maziarka, Lukasz Struski, Przemyslaw Spurek, Jacek Tabor:
Flow-based SVDD for anomaly detection. CoRR abs/2108.04907 (2021) - [i52]Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative Molecule Self-Attention Transformer. CoRR abs/2110.05841 (2021) - [i51]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) - [i50]Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski, Jacek Tabor:
MisConv: Convolutional Neural Networks for Missing Data. CoRR abs/2110.14010 (2021) - [i49]Dawid Rymarczyk, Lukasz Struski, Michal Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski:
Interpretable Image Classification with Differentiable Prototypes Assignment. CoRR abs/2112.02902 (2021) - 2020
- [j26]Lukasz Struski, Marek Smieja, Jacek Tabor:
Pointed Subspace Approach to Incomplete Data. J. Classif. 37(1): 42-57 (2020) - [j25]Stanislaw Jastrzebski, Maciej Szymczak, Agnieszka Pocha, Stefan Mordalski, Jacek Tabor, Andrzej J. Bojarski, Sabina Podlewska:
Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening. J. Chem. Inf. Model. 60(9): 4246-4262 (2020) - [j24]Szymon Knop, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski:
Cramer-Wold Auto-Encoder. J. Mach. Learn. Res. 21: 164:1-164:28 (2020) - [c24]Pawel Morawiecki, Przemyslaw Spurek, Marek Smieja, Jacek Tabor:
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. ESANN 2020: 55-60 - [c23]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. ICLR 2020 - [c22]Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski:
Hypernetwork approach to generating point clouds. ICML 2020: 9099-9108 - [c21]Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski:
Non-linear ICA Based on Cramer-Wold Metric. ICONIP (3) 2020: 294-305 - [c20]Tomasz Danel, Przemyslaw Spurek, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka:
Spatial Graph Convolutional Networks. ICONIP (5) 2020: 668-675 - [c19]Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor:
Finding the Optimal Network Depth in Classification Tasks. ECML/PKDD (3) 2020: 263-278 - [i48]Andrzej Bedychaj, Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor:
WICA: nonlinear weighted ICA. CoRR abs/2001.04147 (2020) - [i47]Lukasz Struski, Szymon Knop, Jacek Tabor, Wiktor Daniec, Przemyslaw Spurek:
LocoGAN - Locally Convolutional GAN. CoRR abs/2002.07897 (2020) - [i46]Lukasz Maziarka, Tomasz Danel, Slawomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanislaw Jastrzebski:
Molecule Attention Transformer. CoRR abs/2002.08264 (2020) - [i45]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. CoRR abs/2002.09572 (2020) - [i44]Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski:
Hypernetwork approach to generating point clouds. CoRR abs/2003.00802 (2020) - [i43]Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor:
Finding the Optimal Network Depth in Classification Tasks. CoRR abs/2004.08172 (2020) - [i42]Dawid Rymarczyk, Jacek Tabor, Bartosz Zielinski:
Kernel Self-Attention in Deep Multiple Instance Learning. CoRR abs/2005.12991 (2020) - [i41]Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski:
HyperFlow: Representing 3D Objects as Surfaces. CoRR abs/2006.08710 (2020) - [i40]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) - [i39]Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak:
Generative models with kernel distance in data space. CoRR abs/2009.07327 (2020) - [i38]Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek:
Flow-based anomaly detection. CoRR abs/2010.03002 (2020) - [i37]Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery. CoRR abs/2011.14340 (2020) - [i36]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
- [j23]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) - [j22]Damian Lesniak, Sabina Podlewska, Stanislaw Jastrzebski, Igor Sieradzki, Andrzej J. Bojarski, Jacek Tabor:
Development of New Methods Needs Proper Evaluation - Benchmarking Sets for Machine Learning Experiments for Class A GPCRs. J. Chem. Inf. Model. 59(12): 4974-4992 (2019) - [j21]Marek Smieja, Lukasz Struski, Jacek Tabor, Mateusz Marzec:
Generalized RBF kernel for incomplete data. Knowl. Based Syst. 173: 150-162 (2019) - [j20]Marek Smieja, Jacek Tabor, Przemyslaw Spurek:
SVM with a neutral class. Pattern Anal. Appl. 22(2): 573-582 (2019) - [j19]Przemyslaw Spurek, Krzysztof Byrski, Jacek Tabor:
Online updating of active function cross-entropy clustering. Pattern Anal. Appl. 22(4): 1409-1425 (2019) - [j18]Lukasz Struski, Przemyslaw Spurek, Jacek Tabor, Marek Smieja:
Projected memory clustering. Pattern Recognit. Lett. 123: 9-15 (2019) - [c18]Wojciech Tarnowski, Piotr Warchol, Stanislaw Jastrzebski, Jacek Tabor, Maciej A. Nowak:
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function. AISTATS 2019: 2221-2230 - [c17]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Jakub Nowak, Marek Smieja:
Hypernetwork Functional Image Representation. ICANN (Workshop) 2019: 496-510 - [c16]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 - [i35]Szymon Knop, Marcin Mazur, Jacek Tabor, Igor T. Podolak, Przemyslaw Spurek:
Sliced generative models. CoRR abs/1901.10417 (2019) - [i34]Bartosz Wójcik, Lukasz Maziarka, Jacek Tabor:
LOSSGRAD: automatic learning rate in gradient descent. CoRR abs/1902.07656 (2019) - [i33]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Marek Smieja, Jakub Nowak:
Multi-task hypernetworks. CoRR abs/1902.10404 (2019) - [i32]Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski:
Non-linear ICA based on Cramer-Wold metric. CoRR abs/1903.00201 (2019) - [i31]Lukasz Struski, Jacek Tabor, Igor T. Podolak, Aleksandra Nowak:
Interpolation in generative models. CoRR abs/1904.03445 (2019) - [i30]Przemyslaw Spurek, Szymon Knop, Jacek Tabor, Igor T. Podolak, Bartosz Wójcik:
One-element Batch Training by Moving Window. CoRR abs/1905.12947 (2019) - [i29]Andrzej Bedychaj, Przemyslaw Spurek, Lukasz Struski, Jacek Tabor:
Independent Component Analysis based on multiple data-weighting. CoRR abs/1906.00028 (2019) - [i28]Pawel Morawiecki, Przemyslaw Spurek, Marek Smieja, Jacek Tabor:
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. CoRR abs/1906.00628 (2019) - [i27]Marek Smieja, Maciej Wolczyk, Jacek Tabor, Bernhard C. Geiger:
SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder. CoRR abs/1906.09333 (2019) - [i26]Przemyslaw Spurek, Tomasz Danel, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka:
Geometric Graph Convolutional Neural Networks. CoRR abs/1909.05310 (2019) - [i25]Maciej Wolczyk, Jacek Tabor, Marek Smieja, Szymon Maszke:
Biologically-Inspired Spatial Neural Networks. CoRR abs/1910.02776 (2019) - 2018
- [j17]Lukasz Struski, Jacek Tabor, Przemyslaw Spurek:
Lossy compression approach to subspace clustering. Inf. Sci. 435: 161-183 (2018) - [j16]Marek Smieja, Oleksandr Myronov, Jacek Tabor:
Semi-supervised discriminative clustering with graph regularization. Knowl. Based Syst. 151: 24-36 (2018) - [j15]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) - [c15]Marek Smieja, Lukasz Struski, Jacek Tabor, Bartosz Zielinski, Przemyslaw Spurek:
Processing of missing data by neural networks. NeurIPS 2018: 2724-2734 - [i24]Bartosz Zielinski, Lukasz Struski, Marek Smieja, Jacek Tabor:
Cascade context encoder for improved inpainting. CoRR abs/1803.04033 (2018) - [i23]Marek Smieja, Lukasz Struski, Jacek Tabor, Bartosz Zielinski, Przemyslaw Spurek:
Processing of missing data by neural networks. CoRR abs/1805.07405 (2018) - [i22]Jacek Tabor, Szymon Knop, Przemyslaw Spurek, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski:
Cramer-Wold AutoEncoder. CoRR abs/1805.09235 (2018) - [i21]Wojciech Tarnowski, Piotr Warchol, Stanislaw Jastrzebski, Jacek Tabor, Maciej A. Nowak:
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function. CoRR abs/1809.08848 (2018) - [i20]Lukasz Maziarka, Marek Smieja, Aleksandra Nowak, Jacek Tabor, Lukasz Struski, Przemyslaw Spurek:
Deep processing of structured data. CoRR abs/1810.01868 (2018) - 2017
- [j14]Przemyslaw Spurek, Jacek Tabor, Krzysztof Byrski:
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