ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2008.08882
  4. Cited By
BOIL: Towards Representation Change for Few-shot Learning

BOIL: Towards Representation Change for Few-shot Learning

20 August 2020
Jaehoon Oh
Hyungjun Yoo
ChangHwan Kim
Seyoung Yun
ArXivPDFHTML

Papers citing "BOIL: Towards Representation Change for Few-shot Learning"

6 / 6 papers shown
Title
Does MAML Only Work via Feature Re-use? A Data Centric Perspective
Does MAML Only Work via Feature Re-use? A Data Centric Perspective
Brando Miranda
Yu-xiong Wang
Oluwasanmi Koyejo
30
4
0
24 Dec 2021
Hybrid Graph Neural Networks for Few-Shot Learning
Hybrid Graph Neural Networks for Few-Shot Learning
Tianyuan Yu
Sen He
Yi-Zhe Song
Tao Xiang
24
59
0
13 Dec 2021
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
177
639
0
19 Sep 2019
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
202
498
0
11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
173
666
0
07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
338
11,684
0
09 Mar 2017
1