Bartłomiej Twardowski

About Bartłomiej Twardowski

Bartłomiej Twardowski, With an exceptional h-index of 11 and a recent h-index of 11 (since 2020), a distinguished researcher at Universidad Autónoma de Barcelona, specializes in the field of computer vision, life long machine learning, recommender systems, artificial intelligence, natural language processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Divide and not forget: Ensemble of selectively trained experts in Continual Learning

Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning

Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning

Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning

GUIDE: Guidance-based Incremental Learning with Diffusion Models

FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning

Icicle: Interpretable class incremental continual learning

Bartłomiej Twardowski Information

University

Position

Computer Vision Center

Citations(all)

1130

Citations(since 2020)

1061

Cited By

200

hIndex(all)

11

hIndex(since 2020)

11

i10Index(all)

12

i10Index(since 2020)

12

Email

University Profile Page

Google Scholar

Bartłomiej Twardowski Skills & Research Interests

computer vision

life long machine learning

recommender systems

artificial intelligence

natural language processing

Top articles of Bartłomiej Twardowski

Title

Journal

Author(s)

Publication Date

Divide and not forget: Ensemble of selectively trained experts in Continual Learning

arXiv preprint arXiv:2401.10191

Grzegorz Rypeść

Sebastian Cygert

Valeriya Khan

Tomasz Trzciński

Bartosz Zieliński

...

2024/1/18

Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning

Alex Gomez-Villa

Bartlomiej Twardowski

Kai Wang

Joost van de Weijer

2024

Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers

Dipam Goswami

Bartłomiej Twardowski

Joost van de Weijer

2024/4/9

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning

Filip Szatkowski

Mateusz Pyla

Marcin Przewięźlikowski

Sebastian Cygert

Bartłomiej Twardowski

...

2024

Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning

arXiv preprint arXiv:2403.07404

Filip Szatkowski

Fei Yang

Bartłomiej Twardowski

Tomasz Trzciński

Joost van de Weijer

2024/3/12

GUIDE: Guidance-based Incremental Learning with Diffusion Models

arXiv preprint arXiv:2403.03938

Bartosz Cywiński

Kamil Deja

Tomasz Trzciński

Bartłomiej Twardowski

Łukasz Kuciński

2024/3/6

FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning

Dipam Goswami

Yuyang Liu

Bartłomiej Twardowski

Joost van de Weijer

2023/12

Icicle: Interpretable class incremental continual learning

Dawid Rymarczyk

Joost van de Weijer

Bartosz Zieliński

Bartłomiej Twardowski

2023/7/23

Augmentation-aware self-supervised learning with guided projector

arXiv preprint arXiv:2306.06082

Marcin Przewięźlikowski

Mateusz Pyla

Bartosz Zieliński

Bartłomiej Twardowski

Jacek Tabor

...

2023/5/31

Bayesian Flow Networks in Continual Learning

arXiv preprint arXiv:2310.12001

Mateusz Pyla

Kamil Deja

Bartłomiej Twardowski

Tomasz Trzciński

2023/10/18

Exploiting graph structured cross-domain representation for multi-domain recommendation

Alejandro Ariza-Casabona

Bartlomiej Twardowski

Tri Kurniawan Wijaya

2023/3/17

Augmentation-aware Self-Supervised Learning with Conditioned Projector

arXiv preprint arXiv:2306.06082

Marcin Przewięźlikowski

Mateusz Pyla

Bartosz Zieliński

Bartłomiej Twardowski

Jacek Tabor

...

2023/5/31

ICICLE: interpretable class incremental continual

Dawid Rymarczyk

Joost van de Weijer

Bartosz Zieliński

Bartłomiej Twardowski

2023

FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems

arXiv preprint arXiv:2309.08635

Francesco Fabbri

Xianghang Liu

Jack R McKenzie

Bartlomiej Twardowski

Tri Kurniawan Wijaya

2023/9/14

Looking through the past: better knowledge retention for generative replay in continual learning

Valeriya Khan

Sebastian Cygert

Bartlomiej Twardowski

Tomasz Trzciński

2023

Revisiting Supervision for Continual Representation Learning

arXiv preprint arXiv:2311.13321

Daniel Marczak

Sebastian Cygert

Tomasz Trzciński

Bartłomiej Twardowski

2023/11/22

Generalized Continual Category Discovery

arXiv preprint arXiv:2308.12112

Daniel Marczak

Grzegorz Rypeść

Sebastian Cygert

Tomasz Trzciński

Bartłomiej Twardowski

2023/8/23

AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation

Damian Sójka

Sebastian Cygert

Bartłomiej Twardowski

Tomasz Trzciński

2023

Technical Report for ICCV 2023 Visual Continual Learning Challenge: Continuous Test-time Adaptation for Semantic Segmentation

arXiv preprint arXiv:2310.13533

Damian Sójka

Yuyang Liu

Dipam Goswami

Sebastian Cygert

Bartłomiej Twardowski

...

2023/10/20

MM-GEF: Multi-modal representation meet collaborative filtering

arXiv preprint arXiv:2308.07222

Hao Wu

Alejandro Ariza-Casabona

Bartłomiej Twardowski

Tri Kurniawan Wijaya

2023/8/14

See List of Professors in Bartłomiej Twardowski University(Universidad Autónoma de Barcelona)