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Bartlomiej Twardowski
Person information
- affiliation: Warsaw University of Technology, Poland
- affiliation: Computer Vision Center Barcelona, Spain
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2020 – today
- 2024
- [j4]Valeriya Khan
, Sebastian Cygert
Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. IEEE Access 12: 45309-45317 (2024) - [j3]Marcin Przewiezlikowski
Augmentation-aware self-supervised learning with conditioned projector. Knowl. Based Syst. 305: 112572 (2024) - [c26]Dipam Goswami, Bartlomiej Twardowski, Joost van de Weijer:
Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers. CVPR Workshops 2024: 4075-4084 - [c25]Dipam Goswami, Albin Soutif-Cormerais, Yuyang Liu, Sandesh Kamath, Bartlomiej Twardowski, Joost van de Weijer:
Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. CVPR 2024: 28525-28534 - [c24]Tomasz Trzcinski
Zero-Waste Machine Learning. ECAI 2024: 43-49 - [c23]Daniel Marczak
Revisiting Supervision for Continual Representation Learning. ECCV (6) 2024: 181-197 - [c22]Grzegorz Rypesc
Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery. ECCV (11) 2024: 320-337 - [c21]Alex Gomez-Villa, Dipam Goswami, Kai Wang, Andrew D. Bagdanov, Bartlomiej Twardowski, Joost van de Weijer:
Exemplar-Free Continual Representation Learning via Learnable Drift Compensation. ECCV (7) 2024: 473-490 - [c20]Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski:
Divide and not forget: Ensemble of selectively trained experts in Continual Learning. ICLR 2024 - [c19]Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer:
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. WACV 2024: 1679-1689 - [c18]Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. WACV 2024: 1966-1976 - [i34]Grzegorz Rypesc
Divide and not forget: Ensemble of selectively trained experts in Continual Learning. CoRR abs/2401.10191 (2024) - [i33]Bartosz Cywinski, Kamil Deja
GUIDE: Guidance-based Incremental Learning with Diffusion Models. CoRR abs/2403.03938 (2024) - [i32]Filip Szatkowski, Fei Yang, Bartlomiej Twardowski, Tomasz Trzcinski, Joost van de Weijer:
Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning. CoRR abs/2403.07404 (2024) - [i31]Dipam Goswami, Bartlomiej Twardowski, Joost van de Weijer:
Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers. CoRR abs/2404.06622 (2024) - [i30]Dipam Goswami, Albin Soutif-Cormerais, Yuyang Liu, Sandesh Kamath, Bartlomiej Twardowski, Joost van de Weijer:
Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. CoRR abs/2405.19074 (2024) - [i29]Daniel Marczak, Bartlomiej Twardowski, Tomasz Trzcinski, Sebastian Cygert:
MagMax: Leveraging Model Merging for Seamless Continual Learning. CoRR abs/2407.06322 (2024) - [i28]Alex Gomez-Villa, Dipam Goswami, Kai Wang, Andrew D. Bagdanov, Bartlomiej Twardowski, Joost van de Weijer:
Exemplar-free Continual Representation Learning via Learnable Drift Compensation. CoRR abs/2407.08536 (2024) - [i27]Sebastian Cygert, Damian Sójka, Tomasz Trzcinski, Bartlomiej Twardowski:
Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection. CoRR abs/2407.14231 (2024) - [i26]Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. CoRR abs/2409.18265 (2024) - 2023
- [j2]Marc Masana
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5513-5533 (2023) - [c17]Alejandro Ariza-Casabona
Exploiting Graph Structured Cross-Domain Representation for Multi-domain Recommendation. ECIR (1) 2023: 49-65 - [c16]Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski:
ICICLE: Interpretable Class Incremental Continual Learning. ICCV 2023: 1887-1898 - [c15]Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. ICCV (Workshops) 2023: 3483-3487 - [c14]Valeriya Khan, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Looking through the past: better knowledge retention for generative replay in continual learning. ICCV (Workshops) 2023: 3488-3492 - [c13]Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. ICCV (Workshops) 2023: 3504-3509 - [c12]Simone Zini, Alex Gomez-Villa, Marco Buzzelli, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer:
Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training. ICLR 2023 - [c11]Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer:
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. NeurIPS 2023 - [i25]Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya:
Exploiting Graph Structured Cross-Domain Representation for Multi-Domain Recommendation. CoRR abs/2302.05990 (2023) - [i24]Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski:
ICICLE: Interpretable Class Incremental Continual Learning. CoRR abs/2303.07811 (2023) - [i23]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) - [i22]Hao Wu, Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya:
MM-GEF: Multi-modal representation meet collaborative filtering. CoRR abs/2308.07222 (2023) - [i21]Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. CoRR abs/2308.09544 (2023) - [i20]Daniel Marczak, Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Generalized Continual Category Discovery. CoRR abs/2308.12112 (2023) - [i19]Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer:
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. CoRR abs/2309.06086 (2023) - [i18]Francesco Fabbri, Xianghang Liu, Jack R. McKenzie, Bartlomiej Twardowski, Tri Kurniawan Wijaya:
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems. CoRR abs/2309.08635 (2023) - [i17]Valeriya Khan, Sebastian Cygert, Kamil Deja
Looking through the past: better knowledge retention for generative replay in continual learning. CoRR abs/2309.10012 (2023) - [i16]Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. CoRR abs/2309.10109 (2023) - [i15]Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer:
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. CoRR abs/2309.14062 (2023) - [i14]Mateusz Pyla, Kamil Deja
Bayesian Flow Networks in Continual Learning. CoRR abs/2310.12001 (2023) - [i13]Damian Sójka, Yuyang Liu, Dipam Goswami, Sebastian Cygert, Bartlomiej Twardowski, Joost van de Weijer:
Technical Report for ICCV 2023 Visual Continual Learning Challenge: Continuous Test-time Adaptation for Semantic Segmentation. CoRR abs/2310.13533 (2023) - [i12]Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Revisiting Supervision for Continual Representation Learning. CoRR abs/2311.13321 (2023) - 2022
- [c10]Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer
Continually Learning Self-Supervised Representations with Projected Functional Regularization. CVPR Workshops 2022: 3866-3876 - [i11]Simone Zini, Marco Buzzelli, Bartlomiej Twardowski, Joost van de Weijer:
Planckian jitter: enhancing the color quality of self-supervised visual representations. CoRR abs/2202.07993 (2022) - [i10]Xianghang Liu, Bartlomiej Twardowski, Tri Kurniawan Wijaya:
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction. CoRR abs/2209.00629 (2022) - 2021
- [c9]Bartlomiej Twardowski
Metric Learning for Session-Based Recommendations. ECIR (1) 2021: 650-665 - [c8]Javad Zolfaghari Bengar, Joost van de Weijer
Reducing Label Effort: Self-Supervised meets Active Learning. ICCVW 2021: 1631-1639 - [i9]Bartlomiej Twardowski, Pawel Zawistowski, Szymon Zaborowski:
Metric Learning for Session-based Recommendations. CoRR abs/2101.02655 (2021) - [i8]Albin Soutif-Cormerais, Marc Masana, Joost van de Weijer, Bartlomiej Twardowski:
On the importance of cross-task features for class-incremental learning. CoRR abs/2106.11930 (2021) - [i7]Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan Raducanu:
Reducing Label Effort: Self-Supervised meets Active Learning. CoRR abs/2108.11458 (2021) - [i6]Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer:
Continually Learning Self-Supervised Representations with Projected Functional Regularization. CoRR abs/2112.15022 (2021) - 2020
- [c7]Lu Yu, Bartlomiej Twardowski
Semantic Drift Compensation for Class-Incremental Learning. CVPR 2020: 6980-6989 - [c6]Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski
Orderless Recurrent Models for Multi-Label Classification. CVPR 2020: 13437-13446 - [c5]Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer:
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. NeurIPS 2020 - [i5]Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer:
Semantic Drift Compensation for Class-Incremental Learning. CoRR abs/2004.00440 (2020) - [i4]Marc Masana
On Class Orderings for Incremental Learning. CoRR abs/2007.02145 (2020) - [i3]Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer:
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. CoRR abs/2007.06271 (2020) - [i2]Marc Masana
Class-incremental learning: survey and performance evaluation. CoRR abs/2010.15277 (2020)
2010 – 2019
- 2019
- [j1]Rafal Biedrzycki
Deep Learning Optimization Tasks and Metaheuristic Methods. Fundam. Informaticae 168(2-4): 185-218 (2019) - [i1]Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer:
Orderless Recurrent Models for Multi-label Classification. CoRR abs/1911.09996 (2019) - 2016
- [c4]Bartlomiej Twardowski
Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks. RecSys 2016: 273-276 - 2015
- [c3]Bartlomiej Twardowski
IoT and Context-Aware Mobile Recommendations Using Multi-agent Systems. WI-IAT (1) 2015: 33-40 - 2014
- [c2]Bartlomiej Twardowski
Multi-agent Architecture for Real-Time Big Data Processing. WI-IAT (3) 2014: 333-337 - 2012
- [c1]Bartlomiej Twardowski, Piotr Gawrysiak
Domain Dependent Product Feature and Opinion Extraction Based on E-Commerce Websites. MISSI 2012: 261-270
Coauthor Index
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last updated on 2024-12-02 21:27 CET by the dblp team
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