Aggregated f-average Neural Network applied to Few-Shot Class Incremental Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Vu, Mathieu, Chouzenoux, Emilie, Ayed, Ismail Ben, Pesquet, Jean-Christophe |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Transductive Zero-Shot and Few-Shot CLIP
by: Martin, Ségolène, et al.
Published: (2024)
by: Martin, Ségolène, et al.
Published: (2024)
Stability Bounds for the Unfolded Forward-Backward Algorithm
by: Chouzenoux, Emilie, et al.
Published: (2024)
by: Chouzenoux, Emilie, et al.
Published: (2024)
A Strong Baseline for Molecular Few-Shot Learning
by: Formont, Philippe, et al.
Published: (2024)
by: Formont, Philippe, et al.
Published: (2024)
Few-Shot Class-Incremental Learning with Prior Knowledge
by: Jiang, Wenhao, et al.
Published: (2024)
by: Jiang, Wenhao, et al.
Published: (2024)
An experimental approach on Few Shot Class Incremental Learning
by: Adam, Marinela
Published: (2025)
by: Adam, Marinela
Published: (2025)
NTK-Guided Few-Shot Class Incremental Learning
by: Liu, Jingren, et al.
Published: (2024)
by: Liu, Jingren, et al.
Published: (2024)
Few-Shot Class-Incremental Learning with Non-IID Decentralized Data
by: Liu, Cuiwei, et al.
Published: (2024)
by: Liu, Cuiwei, et al.
Published: (2024)
Few-Shot Class Incremental Learning via Robust Transformer Approach
by: Paeedeh, Naeem, et al.
Published: (2024)
by: Paeedeh, Naeem, et al.
Published: (2024)
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning
by: Li, Dong, et al.
Published: (2024)
by: Li, Dong, et al.
Published: (2024)
Hyperbolic Coarse-to-Fine Few-Shot Class-Incremental Learning
by: Dai, Jiaxin, et al.
Published: (2025)
by: Dai, Jiaxin, et al.
Published: (2025)
Controllable Forgetting Mechanism for Few-Shot Class-Incremental Learning
by: Paramonov, Kirill, et al.
Published: (2025)
by: Paramonov, Kirill, et al.
Published: (2025)
Does Prior Data Matter? Exploring Joint Training in the Context of Few-Shot Class-Incremental Learning
by: Kim, Shiwon, et al.
Published: (2025)
by: Kim, Shiwon, et al.
Published: (2025)
Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt
by: Liu, Chenxi, et al.
Published: (2024)
by: Liu, Chenxi, et al.
Published: (2024)
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning
by: Zhou, Long, et al.
Published: (2024)
by: Zhou, Long, et al.
Published: (2024)
Sparsity Outperforms Low-Rank Projections in Few-Shot Adaptation
by: Mrabah, Nairouz, et al.
Published: (2025)
by: Mrabah, Nairouz, et al.
Published: (2025)
Variable Bregman Majorization-Minimization Algorithm and its Application to Dirichlet Maximum Likelihood Estimation
by: Martin, Ségolène, et al.
Published: (2025)
by: Martin, Ségolène, et al.
Published: (2025)
Knowledge Adaptation Network for Few-Shot Class-Incremental Learning
by: Wang, Ye, et al.
Published: (2024)
by: Wang, Ye, et al.
Published: (2024)
PKI: Prior Knowledge-Infused Neural Network for Few-Shot Class-Incremental Learning
by: Baoa, Kexin, et al.
Published: (2026)
by: Baoa, Kexin, et al.
Published: (2026)
Compositional Few-Shot Class-Incremental Learning
by: Zou, Yixiong, et al.
Published: (2024)
by: Zou, Yixiong, et al.
Published: (2024)
Efficient Single-Step Framework for Incremental Class Learning in Neural Networks
by: Dopico-Castro, Alejandro, et al.
Published: (2025)
by: Dopico-Castro, Alejandro, et al.
Published: (2025)
Analyse comparative d'algorithmes de restauration en architecture dépliée pour des signaux chromatographiques parcimonieux
by: Gharbi, Mouna, et al.
Published: (2025)
by: Gharbi, Mouna, et al.
Published: (2025)
Enhancing Federated Class-Incremental Learning via Spatial-Temporal Statistics Aggregation
by: Guan, Zenghao, et al.
Published: (2025)
by: Guan, Zenghao, et al.
Published: (2025)
Multimodal Parameter-Efficient Few-Shot Class Incremental Learning
by: D'Alessandro, Marco, et al.
Published: (2023)
by: D'Alessandro, Marco, et al.
Published: (2023)
MolRGen: A Training and Evaluation Setting for De Novo Molecular Generation with Reasonning Models
by: Formont, Philippe, et al.
Published: (2026)
by: Formont, Philippe, et al.
Published: (2026)
On the Impact of Class Imbalance on the Learning Dynamics of Deep Neural Networks:An Intuitive Insight
by: Mustapha, Ismail B., et al.
Published: (2026)
by: Mustapha, Ismail B., et al.
Published: (2026)
Partitioned Memory Storage Inspired Few-Shot Class-Incremental learning
by: Zhang, Renye, et al.
Published: (2025)
by: Zhang, Renye, et al.
Published: (2025)
Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning
by: Ma'sum, M. Anwar, et al.
Published: (2025)
by: Ma'sum, M. Anwar, et al.
Published: (2025)
Learn by Reasoning: Analogical Weight Generation for Few-Shot Class-Incremental Learning
by: Han, Jizhou, et al.
Published: (2025)
by: Han, Jizhou, et al.
Published: (2025)
CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning
by: Oh, Junghun, et al.
Published: (2024)
by: Oh, Junghun, et al.
Published: (2024)
When Sensing Varies with Contexts: Context-as-Transform for Tactile Few-Shot Class-Incremental Learning
by: Lin, Yifeng, et al.
Published: (2026)
by: Lin, Yifeng, et al.
Published: (2026)
Feature-Space Generative Models for One-Shot Class-Incremental Learning
by: Foster, Jack, et al.
Published: (2026)
by: Foster, Jack, et al.
Published: (2026)
An Effective Iterative Solution for Independent Vector Analysis with Convergence Guarantees
by: Cosserat, Clément, et al.
Published: (2024)
by: Cosserat, Clément, et al.
Published: (2024)
Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse
by: He, Kun, et al.
Published: (2025)
by: He, Kun, et al.
Published: (2025)
Cooperative Graph Neural Networks
by: Finkelshtein, Ben, et al.
Published: (2023)
by: Finkelshtein, Ben, et al.
Published: (2023)
CD^2: Constrained Dataset Distillation for Few-Shot Class-Incremental Learning
by: Bao, Kexin, et al.
Published: (2026)
by: Bao, Kexin, et al.
Published: (2026)
Divide and Conquer: Static-Dynamic Collaboration for Few-Shot Class-Incremental Learning
by: Bao, Kexin, et al.
Published: (2026)
by: Bao, Kexin, et al.
Published: (2026)
Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
by: Luthra, Achleshwar, et al.
Published: (2026)
by: Luthra, Achleshwar, et al.
Published: (2026)
Cross-Domain Few-Shot Learning via Adaptive Transformer Networks
by: Paeedeh, Naeem, et al.
Published: (2024)
by: Paeedeh, Naeem, et al.
Published: (2024)
When is an Embedding Model More Promising than Another?
by: Darrin, Maxime, et al.
Published: (2024)
by: Darrin, Maxime, et al.
Published: (2024)
Fair Class-Incremental Learning using Sample Weighting
by: Park, Jaeyoung, et al.
Published: (2024)
by: Park, Jaeyoung, et al.
Published: (2024)
Similar Items
-
Transductive Zero-Shot and Few-Shot CLIP
by: Martin, Ségolène, et al.
Published: (2024) -
Stability Bounds for the Unfolded Forward-Backward Algorithm
by: Chouzenoux, Emilie, et al.
Published: (2024) -
A Strong Baseline for Molecular Few-Shot Learning
by: Formont, Philippe, et al.
Published: (2024) -
Few-Shot Class-Incremental Learning with Prior Knowledge
by: Jiang, Wenhao, et al.
Published: (2024) -
An experimental approach on Few Shot Class Incremental Learning
by: Adam, Marinela
Published: (2025)