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MetaFun: Meta-Learning with Iterative Functional Updates

MetaFun: Meta-Learning with Iterative Functional Updates

5 December 2019
Jin Xu
Jean-François Ton
Hyunjik Kim
Adam R. Kosiorek
Yee Whye Teh
ArXivPDFHTML

Papers citing "MetaFun: Meta-Learning with Iterative Functional Updates"

17 / 17 papers shown
Title
Meta-learning of semi-supervised learning from tasks with heterogeneous
  attribute spaces
Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces
Tomoharu Iwata
Atsutoshi Kumagai
26
2
0
09 Nov 2023
A Closer Look at Few-shot Classification Again
A Closer Look at Few-shot Classification Again
Xu Luo
Hao Wu
Ji Zhang
Lianli Gao
Jing Xu
Jingkuan Song
24
48
0
28 Jan 2023
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior:
  From Theory to Practice
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice
Jonas Rothfuss
Martin Josifoski
Vincent Fortuin
Andreas Krause
43
7
0
14 Nov 2022
BaseTransformers: Attention over base data-points for One Shot Learning
BaseTransformers: Attention over base data-points for One Shot Learning
Mayug Maniparambil
Kevin McGuinness
Noel E. O'Connor
34
3
0
05 Oct 2022
The Neural Process Family: Survey, Applications and Perspectives
The Neural Process Family: Survey, Applications and Perspectives
Saurav Jha
Dong Gong
Xuesong Wang
Richard Turner
L. Yao
BDL
76
24
0
01 Sep 2022
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via
  Sequence Modeling
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
Tung Nguyen
Aditya Grover
BDL
UQCV
19
99
0
09 Jul 2022
Few-Shot Diffusion Models
Few-Shot Diffusion Models
Giorgio Giannone
Didrik Nielsen
Ole Winther
DiffM
183
49
0
30 May 2022
A Comprehensive Survey of Few-shot Learning: Evolution, Applications,
  Challenges, and Opportunities
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities
Yisheng Song
Ting-Yuan Wang
S. Mondal
J. P. Sahoo
SLR
50
344
0
13 May 2022
Neural Processes with Stochastic Attention: Paying more attention to the
  context dataset
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Mingyu Kim
Kyeongryeol Go
Se-Young Yun
29
20
0
11 Apr 2022
Meta-CPR: Generalize to Unseen Large Number of Agents with Communication
  Pattern Recognition Module
Meta-CPR: Generalize to Unseen Large Number of Agents with Communication Pattern Recognition Module
Wei-Cheng Tseng
Wei Wei
Da-Cheng Juan
Min Sun
36
2
0
14 Dec 2021
Non-Gaussian Gaussian Processes for Few-Shot Regression
Non-Gaussian Gaussian Processes for Few-Shot Regression
Marcin Sendera
Jacek Tabor
A. Nowak
Andrzej Bedychaj
Massimiliano Patacchiola
Tomasz Trzciñski
Przemysław Spurek
Maciej Ziȩba
21
19
0
26 Oct 2021
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Xu Luo
Longhui Wei
Liangjiang Wen
Jinrong Yang
Lingxi Xie
Zenglin Xu
Qi Tian
45
87
0
16 Jul 2021
Few-shot Learning for Topic Modeling
Few-shot Learning for Topic Modeling
Tomoharu Iwata
BDL
27
6
0
19 Apr 2021
ReMP: Rectified Metric Propagation for Few-Shot Learning
ReMP: Rectified Metric Propagation for Few-Shot Learning
Yang Zhao
Chunyuan Li
Ping Yu
Changyou Chen
27
6
0
02 Dec 2020
Local Nonparametric Meta-Learning
Local Nonparametric Meta-Learning
Wonjoon Goo
S. Niekum
32
3
0
09 Feb 2020
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
176
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
362
11,700
0
09 Mar 2017
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