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. 2305.07625
  4. Cited By
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn

Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn

12 May 2023
Ondrej Bohdal
Yinbing Tian
Yongshuo Zong
Ruchika Chavhan
Da Li
H. Gouk
Li Guo
Timothy M. Hospedales
ArXivPDFHTML

Papers citing "Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn"

4 / 4 papers shown
Title
UniFS: Universal Few-shot Instance Perception with Point Representations
UniFS: Universal Few-shot Instance Perception with Point Representations
Sheng Jin
Ruijie Yao
Lumin Xu
Wentao Liu
Chao Qian
Ji Wu
Ping Luo
40
2
0
30 Apr 2024
Selecting Relevant Features from a Multi-domain Representation for
  Few-shot Classification
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification
Nikita Dvornik
Cordelia Schmid
Julien Mairal
VLM
167
24
0
20 Mar 2020
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
172
639
0
19 Sep 2019
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
243
11,659
0
09 Mar 2017
1