Recommendation Systems on Million Song Dataset

Metric: nDCG@100 (higher is better)

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#	Model↕	nDCG@100▼	Extra Data	Paper	Date↕	Code
1	EASE	0.389	No	Embarrassingly Shallow Autoencoders for Sparse D...	2019-05-08	Code
2	SANSA	0.388	No	-	-	Code
3	RecVAE	0.326	No	RecVAE: a New Variational Autoencoder for Top-N ...	2019-12-24	Code
4	RaCT	0.319	No	Towards Amortized Ranking-Critical Training for ...	2019-06-10	Code
5	Mult-VAE PR	0.316	No	Variational Autoencoders for Collaborative Filte...	2018-02-16	Code
6	Mult-DAE	0.313	No	Variational Autoencoders for Collaborative Filte...	2018-02-16	Code

#1EASESOTA
0.389
nDCG@100· 2019-05-08
Embarrassingly Shallow Autoencoders for Sparse Data Code
#2SANSA
0.388
nDCG@100
No paperCode
#3RecVAE
0.326
nDCG@100· 2019-12-24
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback Code
#4RaCT
0.319
nDCG@100· 2019-06-10
Towards Amortized Ranking-Critical Training for Collaborative Filtering Code
#5Mult-VAE PRSOTA
0.316
nDCG@100· 2018-02-16
Variational Autoencoders for Collaborative Filtering Code
#6Mult-DAE
0.313
nDCG@100· 2018-02-16
Variational Autoencoders for Collaborative Filtering Code