Recommendation Systems on MovieLens 20M

Metric: nDCG@100 (higher is better)

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#	Model↕	nDCG@100▼	Extra Data	Paper	Date↕	Code
1	VASP	0.448	Yes	Deep Variational Autoencoder with Shallow Parall...	2021-02-10	Code
2	H+Vamp Gated	0.44522	Yes	Enhancing VAEs for Collaborative Filtering: Flex...	2019-11-03	Code
3	RecVAE	0.442	No	RecVAE: a New Variational Autoencoder for Top-N ...	2019-12-24	Code
4	RaCT	0.434	No	Towards Amortized Ranking-Critical Training for ...	2019-06-10	Code
5	Mult-VAE PR	0.426	No	Variational Autoencoders for Collaborative Filte...	2018-02-16	Code
6	EASE	0.42	No	Embarrassingly Shallow Autoencoders for Sparse D...	2019-05-08	Code
7	Mult-DAE	0.419	No	Variational Autoencoders for Collaborative Filte...	2018-02-16	Code

#1VASPSOTA
0.448
nDCG@100· Extra Data· 2021-02-10
Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP)Code
#2H+Vamp GatedSOTA
0.44522
nDCG@100· Extra Data· 2019-11-03
Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating Mechanisms Code
#3RecVAE
0.442
nDCG@100· 2019-12-24
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback Code
#4RaCTSOTA
0.434
nDCG@100· 2019-06-10
Towards Amortized Ranking-Critical Training for Collaborative Filtering Code
#5Mult-VAE PRSOTA
0.426
nDCG@100· 2018-02-16
Variational Autoencoders for Collaborative Filtering Code
#6EASE
0.42
nDCG@100· 2019-05-08
Embarrassingly Shallow Autoencoders for Sparse Data Code
#7Mult-DAE
0.419
nDCG@100· 2018-02-16
Variational Autoencoders for Collaborative Filtering Code