Sae Nad
The implementation of "Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence"
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Neurec | 861 | 2 years ago | 1 | November 04, 2019 | 15 | Python | ||||
| Next RecSys Library | ||||||||||
| Vae_cf | 309 | 6 years ago | 11 | apache-2.0 | Jupyter Notebook | |||||
| Variational autoencoders for collaborative filtering | ||||||||||
| Metarec | 282 | a year ago | 4 | Python | ||||||
| PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models | ||||||||||
| Artificio | 269 | 5 years ago | 3 | apache-2.0 | Python | |||||
| Deep Learning Computer Vision Algorithms for Real-World Use | ||||||||||
| Rnn_recsys | 122 | 5 years ago | 4 | Python | ||||||
| Our implementation of the paper "Embedding-based News Recommendation for Millions of Users" | ||||||||||
| Rectorch | 104 | 4 years ago | 7 | May 27, 2020 | 1 | mit | Python | |||
| rectorch is a pytorch-based framework for state-of-the-art top-N recommendation | ||||||||||
| Collaborative Deep Learning For Recommender Systems | 58 | 6 years ago | Python | |||||||
| The hybrid model combining stacked denoising autoencoder with matrix factorization is applied, to predict the customer purchase behavior in the future month according to the purchase history and user information in the Santander dataset. | ||||||||||
| Recoder | 48 | 3 years ago | 5 | April 10, 2021 | mit | Python | ||||
| Large scale training of factorization models for Collaborative Filtering with PyTorch | ||||||||||
| Gate | 43 | 5 years ago | mit | Python | ||||||
| The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation" | ||||||||||
| Bi Vae | 30 | a year ago | mit | Python | ||||||
| Code for the paper "Bilateral Variational Autoencoder for Collaborative Filtering", WSDM'21 | ||||||||||
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