Incrementally learning new classes with generative classification

Información del proyecto

GenClassifier4CL

Identificador del acuerdo de subvención: 101067759

DOI

10.3030/101067759

Proyecto cerrado

Fecha de la firma de la CE 23 Junio 2022

Fecha de inicio 1 Octubre 2022

Fecha de finalización 30 Septiembre 2024

Financiado con arreglo a

• Marie Skłodowska-Curie Actions (MSCA)

Coste total

Sin datos

Aportación de la UE

€ 191 760,00

Coordinado por

KATHOLIEKE UNIVERSITEIT LEUVEN
Belgium

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

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.

Publicaciones

Conference proceedings (4)

Continual Learning of Diffusion Models with Generative Distillation

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

Prediction Error-based Classification for Class-Incremental Learning

Autores: Michał Zając, Tinne Tuytelaars, Gido M van de Ven
Publicado en: Proceedings of The Twelfth International Conference on Learning Representations - ICLR 2024, 2024
Editor: OpenReview.net

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

Autores: Timm Hess, Tinne Tuytelaars, Gido M van de Ven
Publicado en: Proceedings of the 1st ContinualAI Unconference, 2023, Edición 249, 2024
Editor: PMLR

Continual evaluation for lifelong learning: Identifying the stability gap

Autores: Matthias De Lange, Gido M van de Ven, Tinne Tuytelaars
Publicado en: Proceedings of The Eleventh International Conference on Learning Representations - ICLR 2023, 2023
Editor: OpenReview.net

Peer reviewed articles (1)

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

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

Other (1)

Continual Learning and Catastrophic Forgetting

Autores: Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi
Publicado en: arXiv, 2024
Editor: arXiv
DOI: 10.48550/ARXIV.2403.05175