Jacek Tabor

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 147

Top Venues

Publications

Joanna Waczynska, Piotr Borycki, Slawomir Konrad Tadeja, Jacek Tabor, Przemyslaw Spurek
GaMeS: Mesh-Based Adapting and Modification of Gaussian Splatting. CoRR (2024)
Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski
Relative molecule self-attention transformer. J. Cheminformatics 16 (1) (2024)
Georgii Stanishevskii, Jakub Steczkiewicz, Tomasz Szczepanik, Slawomir Konrad Tadeja, Jacek Tabor, Przemyslaw Spurek
ImplicitDeepfake: Plausible Face-Swapping through Implicit Deepfake Generation using NeRF and Gaussian Splatting. CoRR (2024)
Klaudia Balazy, Lukasz Struski, Marek Smieja, Jacek Tabor
r-softmax: Generalized Softmax with Controllable Sparsity Rate. CoRR (2023)
Adrian Suwala, Bartosz Wójcik, Magdalena Proszewska, Jacek Tabor, Przemyslaw Spurek, Marek Smieja
Face Identity-Aware Disentanglement in StyleGAN. CoRR (2023)
Wojciech Zajac, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek
NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering. CoRR (2023)
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)
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 (2023)
Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek
HyperShot: Few-Shot Learning by Kernel HyperNetworks. WACV (2023)
Klaudia Balazy, Lukasz Struski, Marek Smieja, Jacek Tabor
r-softmax: Generalized Softmax with Controllable Sparsity Rate. ICCS (2) (2023)
Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. WACV (2023)
Lukasz Struski, Tomasz Urbanczyk, Krzysztof Bucki, Bartlomiej Cupial, Aneta Kaczynska, Przemyslaw Spurek, Jacek Tabor
MeVGAN: GAN-based Plugin Model for Video Generation with Applications in Colonoscopy. CoRR (2023)
Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. NeurIPS (2023)
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 (2023)
Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski
Hypernetworks Build Implicit Neural Representations of Sounds. ECML/PKDD (4) (2023)
Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja
ChiENN: Embracing Molecular Chirality with Graph Neural Networks. CoRR (2023)
Dominik Zimny, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation. CoRR (2023)
Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. CoRR (2023)
Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja
ChiENN: Embracing Molecular Chirality with Graph Neural Networks. ECML/PKDD (3) (2023)
Lukasz Struski, Adam Pardyl, Jacek Tabor, Bartosz Zielinski
ProPML: Probability Partial Multi-label Learning. DSAA (2023)
Lukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor, Bartosz Zielinski
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging. CoRR (2023)
Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja
Contrastive Hierarchical Clustering. CoRR (2023)
Mikolaj Sacha, Bartosz Jura, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations. CoRR (2023)
Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja
Contrastive Hierarchical Clustering. ECML/PKDD (1) (2023)
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) (2023)
Dawid Malarz, Weronika Smolak, Jacek Tabor, Slawomir Konrad Tadeja, Przemyslaw Spurek
Gaussian Splatting with NeRF-based Color and Opacity. CoRR (2023)
Marcin Przewiezlikowski, Mateusz Pyla, Bartosz Zielinski, Bartlomiej Twardowski, Jacek Tabor, Marek Smieja
Augmentation-aware Self-supervised Learning with Guided Projector. CoRR (2023)
Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. CoRR (2023)
Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski
Hypernetworks build Implicit Neural Representations of Sounds. CoRR (2023)
Lukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor, Bartosz Zielinski
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging. ECAI (2023)
Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski
SONGs: Self-Organizing Neural Graphs. WACV (2023)
Krzysztof Byrski, Przemyslaw Spurek, Jacek Tabor
Gaussian model for closed curves. CoRR (2023)
Lukasz Struski, Marcin Mazur, Pawel Batorski, Przemyslaw Spurek, Jacek Tabor
Bounding Evidence and Estimating Log-Likelihood in VAE. AISTATS (2023)
Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski, Jacek Tabor
MisConv: Convolutional Neural Networks for Missing Data. WACV (2022)
Dawid Rymarczyk, Lukasz Struski, Michal Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski
Interpretable Image Classification with Differentiable Prototypes Assignment. ECCV (12) (2022)
Piotr Tempczyk, Rafal Michaluk, Lukasz Garncarek, Przemyslaw Spurek, Jacek Tabor, Adam Golinski
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. ICML (2022)
Adriana Borowa, Szczepan Kruczek, Jacek Tabor, Bartosz Zielinski
Weakly-Supervised Cell Classification for Effective High Content Screening. ICCS (1) (2022)
Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek
HyperShot: Few-Shot Learning by Kernel HyperNetworks. CoRR (2022)
Bartosz Wójcik, Jacek Grela, Marek Smieja, Krzysztof Misztal, Jacek Tabor
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier. CoRR (2022)
Piotr Tempczyk, Rafal Michaluk, Lukasz Garncarek, Przemyslaw Spurek, Jacek Tabor, Adam Golinski
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. CoRR (2022)
Lukasz Struski, Marcin Mazur, Pawel Batorski, Przemyslaw Spurek, Jacek Tabor
Bounding Evidence and Estimating Log-Likelihood in VAE. CoRR (2022)
Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak
Generative models with kernel distance in data space. Neurocomputing 487 (2022)
Bartosz Wójcik, Jacek Grela, Marek Smieja, Krzysztof Misztal, Jacek Tabor
SLOVA: Uncertainty estimation using single label one-vs-all classifier. Appl. Soft Comput. 126 (2022)
Piotr Borycki, Piotr Kubacki, Marcin Przewiezlikowski, Tomasz Kusmierczyk, Jacek Tabor, Przemyslaw Spurek
Hypernetwork approach to Bayesian MAML. CoRR (2022)
Andrzej Bedychaj, Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor
Nonlinear Weighted Independent Component Analysis. IPMU (2) (2022)
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)
Lukasz Struski, Szymon Knop, Przemyslaw Spurek, Wiktor Daniec, Jacek Tabor
LocoGAN - Locally convolutional GAN. Comput. Vis. Image Underst. 221 (2022)
Lukasz Struski, Jacek Tabor, Bartosz Zielinski
ProPaLL: Probabilistic Partial Label Learning. CoRR (2022)
Przemyslaw Spurek, Artur Kasymov, M. Mazur, Diana Janik, Slawomir Konrad Tadeja, Lukasz Struski, Jacek Tabor, Tomasz Trzcinski
HyperPocket: Generative Point Cloud Completion. IROS (2022)
Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski
HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks. CoRR (2022)
Szymon Knop, Przemyslaw Spurek, Marcin Mazur, Jacek Tabor, Igor T. Podolak
Batch Size Reconstruction-Distribution Trade-Off In Kernel Based Generative Autoencoders. ICIP (2022)
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 (2022)
Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski
General Hypernetwork Framework for Creating 3D Point Clouds. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Marcin Przewiezlikowski, P. Przybysz, Jacek Tabor, Maciej Zieba, Przemyslaw Spurek
HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks. CoRR (2022)
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) (2022)
Marcin Sendera, Marek Smieja, Lukasz Maziarka, Lukasz Struski, Przemyslaw Spurek, Jacek Tabor
Flow-based SVDD for anomaly detection. CoRR (2021)
Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification. KDD (2021)
Przemyslaw Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Slawomir K. Tadeja, Lukasz Struski, Jacek Tabor, Tomasz Trzcinski
HyperPocket: Generative Point Cloud Completion. CoRR (2021)
Dawid Rymarczyk, Lukasz Struski, Michal Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski
Interpretable Image Classification with Differentiable Prototypes Assignment. CoRR (2021)
Bartosz Wójcik, Pawel Morawiecki, Marek Smieja, Tomasz Krzyzek, Przemyslaw Spurek, Jacek Tabor
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders. ICTAI (2021)
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)
Klaudia Balazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor, Karl Aberer
Direction is what you need: Improving Word Embedding Compression in Large Language Models. CoRR (2021)
Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski
SONG: Self-Organizing Neural Graphs. CoRR (2021)
Marek Smieja, Maciej Wolczyk, Jacek Tabor, Bernhard C. Geiger
SeGMA: Semi-Supervised Gaussian Mixture Autoencoder. IEEE Trans. Neural Networks Learn. Syst. 32 (9) (2021)
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 (2021)
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)
Agnieszka Pocha, Tomasz Danel, Sabina Podlewska, Jacek Tabor, Lukasz Maziarka
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. IJCNN (2021)
Jakub Bielawski, Jacek Tabor
Convex hull of a fuzzy set and triangular norms. Fuzzy Sets Syst. 417 (2021)
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 (2021)
Marcin Przewiezlikowski, Marek Smieja, Lukasz Struski, Jacek Tabor
MisConv: Convolutional Neural Networks for Missing Data. CoRR (2021)
Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel Morkisz, Stanislaw Jastrzebski
Relative Molecule Self-Attention Transformer. CoRR (2021)
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)
Dawid Rymarczyk, Adriana Borowa, Jacek Tabor, Bartosz Zielinski
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning. WACV (2021)
Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery. CoRR (2020)
Dawid Rymarczyk, Jacek Tabor, Bartosz Zielinski
Kernel Self-Attention in Deep Multiple Instance Learning. CoRR (2020)
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 (2020)
Lukasz Struski, Marek Smieja, Jacek Tabor
Pointed Subspace Approach to Incomplete Data. J. Classif. 37 (1) (2020)
Szymon Knop, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski
Cramer-Wold Auto-Encoder. J. Mach. Learn. Res. 21 (2020)
Bartosz Wójcik, Pawel Morawiecki, Marek Smieja, Tomasz Krzyzek, Przemyslaw Spurek, Jacek Tabor
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders. CoRR (2020)
Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak
Generative models with kernel distance in data space. CoRR (2020)
Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski
Hypernetwork approach to generating point clouds. CoRR (2020)
Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek
Flow-based anomaly detection. CoRR (2020)
Lukasz Maziarka, Tomasz Danel, Slawomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanislaw Jastrzebski
Molecule Attention Transformer. CoRR (2020)
Maciej Zieba, Marcin Przewiezlikowski, Marek Smieja, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek
RegFlow: Probabilistic Flow-based Regression for Future Prediction. CoRR (2020)
Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski
Hypernetwork approach to generating point clouds. ICML (2020)
Lukasz Struski, Szymon Knop, Jacek Tabor, Wiktor Daniec, Przemyslaw Spurek
LocoGAN - Locally Convolutional GAN. CoRR (2020)
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) (2020)
Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski
Non-linear ICA Based on Cramer-Wold Metric. ICONIP (3) (2020)
Tomasz Danel, Przemyslaw Spurek, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka
Spatial Graph Convolutional Networks. ICONIP (5) (2020)
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)
Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski
HyperFlow: Representing 3D Objects as Surfaces. CoRR (2020)
Andrzej Bedychaj, Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor
WICA: nonlinear weighted ICA. CoRR (2020)
Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor
Finding the Optimal Network Depth in Classification Tasks. ECML/PKDD (3) (2020)
Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor
Finding the Optimal Network Depth in Classification Tasks. CoRR (2020)
Pawel Morawiecki, Przemyslaw Spurek, Marek Smieja, Jacek Tabor
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. ESANN (2020)
Lukasz Struski, Przemyslaw Spurek, Jacek Tabor, Marek Smieja
Projected memory clustering. Pattern Recognit. Lett. 123 (2019)
Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski
Non-linear ICA based on Cramer-Wold metric. CoRR (2019)
Marek Smieja, Krzysztof Hajto, Jacek Tabor
Efficient mixture model for clustering of sparse high dimensional binary data. Data Min. Knowl. Discov. 33 (6) (2019)
Przemyslaw Spurek, Szymon Knop, Jacek Tabor, Igor T. Podolak, Bartosz Wójcik
One-element Batch Training by Moving Window. CoRR (2019)
Przemyslaw Spurek, Tomasz Danel, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka
Geometric Graph Convolutional Neural Networks. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jacek Tabor