Domain Dependent Product Feature and Opinion Extraction Based on E-Commerce Websites. - Bartlomiej Twardowski; Piotr Gawrysiak (MISSI, 2012)

Multi-agent Architecture for Real-Time Big Data Processing. - Bartlomiej Twardowski; Dominik Ryzko (WI-IAT (3), 2014)

IoT and Context-Aware Mobile Recommendations Using Multi-agent Systems. - Bartlomiej Twardowski; Dominik Ryzko (WI-IAT (1), 2015)

Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks. - Bartlomiej Twardowski (RecSys, 2016)

Deep Learning Optimization Tasks and Metaheuristic Methods. - Rafal Biedrzycki; Pawel Zawistowski; Bartlomiej Twardowski (Fundam. Informaticae, 2019)

Semantic Drift Compensation for Class-Incremental Learning. - Lu Yu 004; Bartlomiej Twardowski; Xialei Liu; Luis Herranz; Kai Wang 060; Yongmei Cheng; Shangling Jui; Joost van de Weijer 001 (CVPR, 2020)

Orderless Recurrent Models for Multi-Label Classification. - Vacit Oguz Yazici; Abel Gonzalez-Garcia; Arnau Ramisa; Bartlomiej Twardowski; Joost van de Weijer 001 (CVPR, 2020)

RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. - Riccardo Del Chiaro; Bartlomiej Twardowski; Andrew D. Bagdanov; Joost van de Weijer 001 (NeurIPS, 2020)

On Class Orderings for Incremental Learning. - Marc Masana; Bartlomiej Twardowski; Joost van de Weijer 001 (CoRR, 2020)

Class-incremental learning: survey and performance evaluation. - Marc Masana; Xialei Liu; Bartlomiej Twardowski; Mikel Menta; Andrew D. Bagdanov; Joost van de Weijer 001 (CoRR, 2020)

Metric Learning for Session-Based Recommendations. - Bartlomiej Twardowski; Pawel Zawistowski; Szymon Zaborowski (ECIR (1), 2021)

Reducing Label Effort: Self-Supervised meets Active Learning. - Javad Zolfaghari Bengar; Joost van de Weijer 001; Bartlomiej Twardowski; Bogdan Raducanu (ICCVW, 2021)

On the importance of cross-task features for class-incremental learning. - Albin Soutif-Cormerais; Marc Masana; Joost van de Weijer 001; Bartlomiej Twardowski (CoRR, 2021)

Continually Learning Self-Supervised Representations with Projected Functional Regularization. - Alex Gomez-Villa; Bartlomiej Twardowski; Lu Yu 004; Andrew D. Bagdanov; Joost van de Weijer 001 (CVPR Workshops, 2022)

Planckian jitter: enhancing the color quality of self-supervised visual representations. - Simone Zini; Marco Buzzelli; Bartlomiej Twardowski; Joost van de Weijer 001 (CoRR, 2022)

Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction. - Xianghang Liu; Bartlomiej Twardowski; Tri Kurniawan Wijaya (CoRR, 2022)

Exploiting Graph Structured Cross-Domain Representation for Multi-domain Recommendation. - Alejandro Ariza-Casabona; Bartlomiej Twardowski; Tri Kurniawan Wijaya (ECIR (1), 2023)

ICICLE: Interpretable Class Incremental Continual Learning. - Dawid Rymarczyk; Joost van de Weijer 001; Bartosz Zielinski 001; Bartlomiej Twardowski (ICCV, 2023)

Looking through the past: better knowledge retention for generative replay in continual learning. - Valeriya Khan; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski (ICCV (Workshops), 2023)

AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. - Damian Sójka; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski (ICCV (Workshops), 2023)

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. - Filip Szatkowski; Mateusz Pyla; Marcin Przewiezlikowski; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski (ICCV (Workshops), 2023)

Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training. - Simone Zini; Alex Gomez-Villa; Marco Buzzelli; Bartlomiej Twardowski; Andrew D. Bagdanov; Joost van de Weijer 001 (ICLR, 2023)

FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. - Dipam Goswami; Yuyang Liu; Bartlomiej Twardowski; Joost van de Weijer 001 (NeurIPS, 2023)

Augmentation-aware Self-supervised Learning with Guided Projector. - Marcin Przewiezlikowski; Mateusz Pyla; Bartosz Zielinski 001; Bartlomiej Twardowski; Jacek Tabor; Marek Smieja (CoRR, 2023)

MM-GEF: Multi-modal representation meet collaborative filtering. - Hao Wu; Alejandro Ariza-Casabona; Bartlomiej Twardowski; Tri Kurniawan Wijaya (CoRR, 2023)

Generalized Continual Category Discovery. - Daniel Marczak; Grzegorz Rypesc; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (CoRR, 2023)

FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems. - Francesco Fabbri; Xianghang Liu; Jack R. McKenzie; Bartlomiej Twardowski; Tri Kurniawan Wijaya (CoRR, 2023)

Bayesian Flow Networks in Continual Learning. - Mateusz Pyla; Kamil Deja; Bartlomiej Twardowski; Tomasz Trzcinski (CoRR, 2023)

Technical Report for ICCV 2023 Visual Continual Learning Challenge: Continuous Test-time Adaptation for Semantic Segmentation. - Damian Sójka; Yuyang Liu; Dipam Goswami; Sebastian Cygert; Bartlomiej Twardowski; Joost van de Weijer 001 (CoRR, 2023)

Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. - Marc Masana; Xialei Liu; Bartlomiej Twardowski; Mikel Menta; Andrew D. Bagdanov; Joost van de Weijer 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. - Dipam Goswami; Albin Soutif-Cormerais; Yuyang Liu; Sandesh Kamath; Bartlomiej Twardowski; Joost van de Weijer 001 (CVPR, 2024)

Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers. - Dipam Goswami; Bartlomiej Twardowski; Joost van de Weijer 001 (CVPR Workshops, 2024)

Zero-Waste Machine Learning. - Tomasz Trzcinski; Bartlomiej Twardowski; Bartosz Zielinski 001; Kamil Adamczewski; Bartosz Wójcik (ECAI, 2024)

Exemplar-Free Continual Representation Learning via Learnable Drift Compensation. - Alex Gomez-Villa; Dipam Goswami; Kai Wang 060; Andrew D. Bagdanov; Bartlomiej Twardowski; Joost van de Weijer 001 (ECCV (7), 2024)

Revisiting Supervision for Continual Representation Learning. - Daniel Marczak; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (ECCV (6), 2024)

MAGMAX: Leveraging Model Merging for Seamless Continual Learning. - Daniel Marczak; Bartlomiej Twardowski; Tomasz Trzcinski; Sebastian Cygert (ECCV (85), 2024)

Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery. - Grzegorz Rypesc; Daniel Marczak; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (ECCV (11), 2024)

Divide and not forget: Ensemble of selectively trained experts in Continual Learning. - Grzegorz Rypesc; Sebastian Cygert; Valeriya Khan; Tomasz Trzcinski; Bartosz Zielinski 001; Bartlomiej Twardowski (ICLR, 2024)

Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. - Grzegorz Rypesc; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (NeurIPS, 2024)

Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. - Alex Gomez-Villa; Bartlomiej Twardowski; Kai Wang 060; Joost van de Weijer 001 (WACV, 2024)

Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. - Valeriya Khan; Sebastian Cygert; Kamil Deja; Tomasz Trzcinski; Bartlomiej Twardowski (IEEE Access, 2024)

GUIDE: Guidance-based Incremental Learning with Diffusion Models. - Bartosz Cywinski; Kamil Deja; Tomasz Trzcinski; Bartlomiej Twardowski; Lukasz Kucinski (CoRR, 2024)

Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning. - Filip Szatkowski; Fei Yang 004; Bartlomiej Twardowski; Tomasz Trzcinski; Joost van de Weijer 001 (CoRR, 2024)

Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection. - Sebastian Cygert; Damian Sójka; Tomasz Trzcinski; Bartlomiej Twardowski (CoRR, 2024)

Covariances for Free: Exploiting Mean Distributions for Federated Learning with Pre-Trained Models. - Dipam Goswami; Simone Magistri; Kai Wang 060; Bartlomiej Twardowski; Andrew D. Bagdanov; Joost van de Weijer 001 (CoRR, 2024)

Augmentation-aware self-supervised learning with conditioned projector. - Marcin Przewiezlikowski; Mateusz Pyla; Bartosz Zielinski 001; Bartlomiej Twardowski; Jacek Tabor; Marek Smieja (Knowl. Based Syst., 2024)

The Art of Deception: Color Visual Illusions and Diffusion Models. - Alexandra Gomez-Villa; Kai Wang 060; C. Alejandro Párraga; Bartlomiej Twardowski; Jesus Malo; Javier Vazquez-Corral; Joost van de Weijer 001 (CVPR, 2025)

No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces. - Daniel Marczak; Simone Magistri; Sebastian Cygert; Bartlomiej Twardowski; Andrew D. Bagdanov; Joost van de Weijer 001 (CoRR, 2025)

Query Drift Compensation: Enabling Compatibility in Continual Learning of Retrieval Embedding Models. - Dipam Goswami; Liying Wang; Bartlomiej Twardowski; Joost van de Weijer 001 (CoRR, 2025)

Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual Learning. - Stanislaw Pawlak; Bartlomiej Twardowski; Tomasz Trzcinski; Joost van de Weijer 001 (CoRR, 2025)