MetaFun: meta-learning with iterative functional updates
We develop a functional encoder-decoder approach to supervised meta-learning, where labeled data is encoded into an infinite-dimensional functional representation rather than a finite-dimensional one. Furthermore, rather than directly producing the representation, we learn a neural update rule resem...
Main Authors: | Xu, J, Ton, J-F, Kim, H, Kosiorek, AR, Teh, YW |
---|---|
פורמט: | Journal article |
שפה: | English |
יצא לאור: |
MLResearch Press
2020
|
פריטים דומים
-
MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis
מאת: Pablo Malmierca-Merlo, et al.
יצא לאור: (2024-08-01) -
Correction: MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis
מאת: Pablo Malmierca-Merlo, et al.
יצא לאור: (2024-09-01) -
Noise contrastive meta-learning for conditional density estimation using kernel mean embeddings
מאת: Ton, J-F, et al.
יצא לאור: (2021) -
Set transformer: A framework for attention-based permutation-invariant neural networks
מאת: Lee, J, et al.
יצא לאור: (2019) -
Model updating for fun kart chassis
מאת: Mohd Sahril, Mohd Fouzi
יצא לאור: (2008)