Image de couverture de livre

Incremental Learning with Repetition via Pseudo-Feature Projection

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Tscheschner, Benedikt, Veas, Eduardo, Masana, Marc
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Feature Expansion and enhanced Compression for Class Incremental Learning
par: Ferdinand, Quentin, et autres
Publié: (2024)

Continual Learning in the Presence of Repetition
par: Hemati, Hamed, et autres
Publié: (2024)

Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning
par: He, Run, et autres
Publié: (2025)

Feature-Space Generative Models for One-Shot Class-Incremental Learning
par: Foster, Jack, et autres
Publié: (2026)

Class Incremental Learning via Likelihood Ratio Based Task Prediction
par: Lin, Haowei, et autres
Publié: (2023)

Unsupervised Video Class-Incremental Learning via Deep Embedded Clustering Management
par: Kurpukdee, Nattapong, et autres
Publié: (2026)

One-Shot Domain Incremental Learning
par: Esaki, Yasushi, et autres
Publié: (2024)

Prediction Error-based Classification for Class-Incremental Learning
par: Zając, Michał, et autres
Publié: (2023)

OVR: A Dataset for Open Vocabulary Temporal Repetition Counting in Videos
par: Dwibedi, Debidatta, et autres
Publié: (2024)

PLUM: Improving Inference Efficiency By Leveraging Repetition-Sparsity Trade-Off
par: Kuhar, Sachit, et autres
Publié: (2023)

Merge and Bound: Direct Manipulations on Weights for Class Incremental Learning
par: Kim, Taehoon, et autres
Publié: (2025)

Buffer-free Class-Incremental Learning with Out-of-Distribution Detection
par: Gupta, Srishti, et autres
Publié: (2025)

Hyperbolic Coarse-to-Fine Few-Shot Class-Incremental Learning
par: Dai, Jiaxin, et autres
Publié: (2025)

Controllable Forgetting Mechanism for Few-Shot Class-Incremental Learning
par: Paramonov, Kirill, et autres
Publié: (2025)

Dynamic Integration of Task-Specific Adapters for Class Incremental Learning
par: Li, Jiashuo, et autres
Publié: (2024)

PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning
par: Ma'sum, Muhammad Anwar, et autres
Publié: (2024)

A Short Note on Evaluating RepNet for Temporal Repetition Counting in Videos
par: Dwibedi, Debidatta, et autres
Publié: (2024)

Domain Incremental Learning for Pandemic-Resilient Chest X-Ray Analysis
par: Kim, Danu
Publié: (2026)

Continual Adapter Tuning with Semantic Shift Compensation for Class-Incremental Learning
par: Zhou, Qinhao, et autres
Publié: (2024)

Mitigating Interference in the Knowledge Continuum through Attention-Guided Incremental Learning
par: Bhat, Prashant, et autres
Publié: (2024)

CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning
par: Frascaroli, Emanuele, et autres
Publié: (2024)

Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning
par: Cao, Xusheng, et autres
Publié: (2025)

CCSI: Continual Class-Specific Impression for Data-free Class Incremental Learning
par: Ayromlou, Sana, et autres
Publié: (2024)

Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method
par: Jeeveswaran, Kishaan, et autres
Publié: (2024)

Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt
par: Liu, Chenxi, et autres
Publié: (2024)

Unsupervised Active Learning via Natural Feature Progressive Framework
par: Liu, Yuxi, et autres
Publié: (2025)

Expectation Maximization Pseudo Labels
par: Xu, Moucheng, et autres
Publié: (2023)

Energy Correction Model in the Feature Space for Out-of-Distribution Detection
par: Lafon, Marc, et autres
Publié: (2024)

GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning
par: Kim, Minsu, et autres
Publié: (2025)

Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach
par: Rai, Ayush K., et autres
Publié: (2023)

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations
par: Alkin, Benedikt, et autres
Publié: (2024)

Learning Robust Convolutional Neural Networks with Relevant Feature Focusing via Explanations
par: Adachi, Kazuki, et autres
Publié: (2022)

Generative Multi-modal Models are Good Class-Incremental Learners
par: Cao, Xusheng, et autres
Publié: (2024)

Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning
par: Ma'sum, M. Anwar, et autres
Publié: (2025)

Walking the Web of Concept-Class Relationships in Incrementally Trained Interpretable Models
par: Agrawal, Susmit, et autres
Publié: (2025)

Contrastive Regularization over LoRA for Multimodal Biomedical Image Incremental Learning
par: Zhang, Haojie, et autres
Publié: (2025)

SEAL: Searching Expandable Architectures for Incremental Learning
par: Gambella, Matteo, et autres
Publié: (2025)

Learning by Reconstruction Produces Uninformative Features For Perception
par: Balestriero, Randall, et autres
Publié: (2024)

Pseudo-Simulation for Autonomous Driving
par: Cao, Wei, et autres
Publié: (2025)

CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation
par: Zhou, Chenliang, et autres
Publié: (2022)