Lecture on Deep Meta-Learning (MAML, Matching network, Prototypical network)

Stanford CS330 Deep Multi-Task & Meta Learning - Non-Parametric Few-Shot Learning l 2022 I Lecture 6Подробнее

Prototypical Networks for Domain Adaptation in Acoustic Scene Classification. ICASSP-2021. Shubhr S.Подробнее

Prototypical NetworkПодробнее

Part 1: Matching NetsПодробнее

Stanford CS330: Deep Multi-task & Meta Learning | 2020 | Lecture 6: Non-Parametric Few-Shot LearningПодробнее

Model Agnostic Meta Learning (MAML) | Machine LearningПодробнее

[Few-shot learning][2.0] literature review (MAML, ProtoNets, RelationNets, etc)Подробнее

CS 182: Lecture 21: Part 1: Meta-LearningПодробнее

[Few-shot learning][2.2] Prototypical Networks: intuition, algorithm, pytorch codeПодробнее

[Few-shot learning][2.4] MAML: Model-Agnostic Meta-LearningПодробнее

CVPR 2023 Bi-level Meta-learning for Few-shot Domain GeneralizationПодробнее

Summary Paper: Prototypical Networks for Few-shot LearningПодробнее

Few-shot Learning | Lecture 72 (Part 2) | Applied Deep Learning (Supplementary)Подробнее

Toward Efficient Learning: Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksПодробнее

FSL: Few Shot Learning, Prototypical NetworkПодробнее

DDN Invited Talk: Meta-Learning Beyond Few-Shot Classification (Chelsea Finn)Подробнее

Master's student Gunshi Gupta presenting "La-MAML: Look-ahead Meta Learning for Continual Learning"Подробнее