Incrementally learning new classes with generative classification

Informazioni relative al progetto

GenClassifier4CL

ID dell’accordo di sovvenzione: 101067759

DOI

10.3030/101067759

Progetto chiuso

Data della firma CE 23 Giugno 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2024

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 191 760,00

Coordinato da

KATHOLIEKE UNIVERSITEIT LEUVEN
Belgium

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I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (2)

Communication, Dissemination & Outreach Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Career Development Plan

A Career Development Plan will be established jointly by the supervisor(s) and the researcher. In addition to research objectives, this plan will comprise the researcher's training and career needs, including training on transferable skills, teaching, planning for publications and participation in conferences and events aiming at opening science and research to citizens. The Plan can be updated when needed.

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected, processed or generated by the action. It is a document describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Pubblicazioni

Conference proceedings (4)

Continual Learning of Diffusion Models with Generative Distillation

Autori: Sergi Masip, Pau Rodriguez, Tinne Tuytelaars, Gido M van de Ven
Pubblicato in: Proceedings of The 3rd Conference on Lifelong Learning Agents (CoLLAs), 2024
Editore: To appear in PMLR

Prediction Error-based Classification for Class-Incremental Learning

Autori: Michał Zając, Tinne Tuytelaars, Gido M van de Ven
Pubblicato in: Proceedings of The Twelfth International Conference on Learning Representations - ICLR 2024, 2024
Editore: OpenReview.net

Two Complementary Perspectives to Continual Learning: Ask Not Only What to Optimize, But Also How

Autori: Timm Hess, Tinne Tuytelaars, Gido M van de Ven
Pubblicato in: Proceedings of the 1st ContinualAI Unconference, 2023, Numero 249, 2024
Editore: PMLR

Continual evaluation for lifelong learning: Identifying the stability gap

Autori: Matthias De Lange, Gido M van de Ven, Tinne Tuytelaars
Pubblicato in: Proceedings of The Eleventh International Conference on Learning Representations - ICLR 2023, 2023
Editore: OpenReview.net

Peer reviewed articles (1)

Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting

Autori: Timm Hess, Eli Verwimp, Gido M van de Ven, Tinne Tuytelaars
Pubblicato in: Transactions on Machine Learning Research (TMLR), 2024, ISSN 2835-8856
Editore: TMLR
DOI: 10.48550/arXiv.2304.00933

Other (1)

Continual Learning and Catastrophic Forgetting

Autori: Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi
Pubblicato in: arXiv, 2024
Editore: arXiv
DOI: 10.48550/ARXIV.2403.05175