Bartlomiej Twardowski

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 54

Top Topics

Active Learning

Incremental Learning

Semantic Segmentation

Top Venues

ICCV (Workshops)

Publications

Dipam Goswami, Bartlomiej Twardowski, Joost van de Weijer
Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers. CoRR (2024)
Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski
Divide and not forget: Ensemble of selectively trained experts in Continual Learning. CoRR (2024)
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 (2024)
Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski
Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. IEEE Access 12 (2024)
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)
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)
Daniel Marczak, Bartlomiej Twardowski, Tomasz Trzcinski, Sebastian Cygert
MagMax: Leveraging Model Merging for Seamless Continual Learning. CoRR (2024)
Sebastian Cygert, Damian Sójka, Tomasz Trzcinski, Bartlomiej Twardowski
Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection. CoRR (2024)
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 (2024)
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 (2024)
Bartosz Cywinski, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski, Lukasz Kucinski
GUIDE: Guidance-based Incremental Learning with Diffusion Models. CoRR (2024)
Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. WACV (2024)
Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. CoRR (2023)
Mateusz Pyla, Kamil Deja, Bartlomiej Twardowski, Tomasz Trzcinski
Bayesian Flow Networks in Continual Learning. CoRR (2023)
Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. CoRR (2023)
Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. CoRR (2023)
Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski
Looking through the past: better knowledge retention for generative replay in continual learning. CoRR (2023)
Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya
Exploiting Graph Structured Cross-Domain Representation for Multi-domain Recommendation. ECIR (1) (2023)
Hao Wu, Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya
MM-GEF: Multi-modal representation meet collaborative filtering. CoRR (2023)
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)
Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
Revisiting Supervision for Continual Representation Learning. CoRR (2023)
Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya
Exploiting Graph Structured Cross-Domain Representation for Multi-Domain Recommendation. CoRR (2023)
Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. ICCV (Workshops) (2023)
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 (2023)
Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski
ICICLE: Interpretable Class Incremental Continual Learning. ICCV (2023)
Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. CoRR (2023)
Daniel Marczak, Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
Generalized Continual Category Discovery. CoRR (2023)
Francesco Fabbri, Xianghang Liu, Jack R. McKenzie, Bartlomiej Twardowski, Tri Kurniawan Wijaya
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems. CoRR (2023)
Valeriya Khan, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
Looking through the past: better knowledge retention for generative replay in continual learning. ICCV (Workshops) (2023)
Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45 (5) (2023)
Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski
ICICLE: Interpretable Class Incremental Continual Learning. CoRR (2023)
Marcin Przewiezlikowski, Mateusz Pyla, Bartosz Zielinski, Bartlomiej Twardowski, Jacek Tabor, Marek Smieja
Augmentation-aware Self-supervised Learning with Guided Projector. CoRR (2023)
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)
Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. NeurIPS (2023)
Xianghang Liu, Bartlomiej Twardowski, Tri Kurniawan Wijaya
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction. CoRR (2022)
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)
Simone Zini, Marco Buzzelli, Bartlomiej Twardowski, Joost van de Weijer
Planckian jitter: enhancing the color quality of self-supervised visual representations. CoRR (2022)
Bartlomiej Twardowski, Pawel Zawistowski, Szymon Zaborowski
Metric Learning for Session-based Recommendations. CoRR (2021)
Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan C. Raducanu
Reducing Label Effort: Self-Supervised meets Active Learning. CoRR (2021)
Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan C. Raducanu
Reducing Label Effort: Self-Supervised meets Active Learning. ICCVW (2021)
Albin Soutif-Cormerais, Marc Masana, Joost van de Weijer, Bartlomiej Twardowski
On the importance of cross-task features for class-incremental learning. CoRR (2021)
Bartlomiej Twardowski, Pawel Zawistowski, Szymon Zaborowski
Metric Learning for Session-Based Recommendations. ECIR (1) (2021)
Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer
Continually Learning Self-Supervised Representations with Projected Functional Regularization. CoRR (2021)
Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer
Orderless Recurrent Models for Multi-Label Classification. CVPR (2020)
Marc Masana, Bartlomiej Twardowski, Joost van de Weijer
On Class Orderings for Incremental Learning. CoRR (2020)
Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer
Class-incremental learning: survey and performance evaluation. CoRR (2020)
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. CVPR (2020)
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 (2020)
Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. NeurIPS (2020)
Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. CoRR (2020)
Rafal Biedrzycki, Pawel Zawistowski, Bartlomiej Twardowski
Deep Learning Optimization Tasks and Metaheuristic Methods. Fundam. Informaticae 168 (2-4) (2019)
Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer
Orderless Recurrent Models for Multi-label Classification. CoRR (2019)
Bartlomiej Twardowski
Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks. RecSys (2016)
Bartlomiej Twardowski, Dominik Ryzko
IoT and Context-Aware Mobile Recommendations Using Multi-agent Systems. WI-IAT (1) (2015)
Bartlomiej Twardowski, Dominik Ryzko
Multi-agent Architecture for Real-Time Big Data Processing. WI-IAT (3) (2014)
Bartlomiej Twardowski, Piotr Gawrysiak
Domain Dependent Product Feature and Opinion Extraction Based on E-Commerce Websites. MISSI (2012)