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. 2202.01339
  4. Cited By
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity
  and Few-Shot Difficulty

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

1 February 2022
Jaehoon Oh
Sungnyun Kim
Namgyu Ho
Jin-Hwa Kim
Hwanjun Song
Se-Young Yun
ArXivPDFHTML

Papers citing "Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty"

10 / 10 papers shown
Title
Closed-form merging of parameter-efficient modules for Federated Continual Learning
Closed-form merging of parameter-efficient modules for Federated Continual Learning
Riccardo Salami
Pietro Buzzega
Matteo Mosconi
Jacopo Bonato
Luigi Sabetta
Simone Calderara
FedML
MoMe
CLL
31
2
0
23 Oct 2024
CLIP with Generative Latent Replay: a Strong Baseline for Incremental
  Learning
CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning
Emanuele Frascaroli
Aniello Panariello
Pietro Buzzega
Lorenzo Bonicelli
Angelo Porrello
Simone Calderara
VLM
CLL
35
3
0
22 Jul 2024
Exploring Cross-Domain Few-Shot Classification via Frequency-Aware
  Prompting
Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting
Tiange Zhang
Qing Cai
Feng Gao
Lin Qi
Junyu Dong
22
1
0
24 Jun 2024
Few and Fewer: Learning Better from Few Examples Using Fewer Base
  Classes
Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes
Raphael Lafargue
Yassir Bendou
Bastien Pasdeloup
J. Diguet
Ian Reid
Vincent Gripon
Jack Valmadre
17
0
0
29 Jan 2024
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through
  Text Reconstruction
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction
Qingyun Wang
Zixuan Zhang
Hongxiang Li
Xuan Liu
Jiawei Han
Huimin Zhao
Heng Ji
41
1
0
18 Jan 2024
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
138
278
0
12 Feb 2021
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
238
3,359
0
09 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
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
165
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
243
11,659
0
09 Mar 2017
1