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19 search results found
Awesome Recsys Papers
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614
The awesome and classic papers in recommendation system!!! Good luck to every RecSys-learner!
Awesome Recsys
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351
A curated list of awesome Recommender System (Books, Conferences, Researchers, Papers, Github Repositories, Useful Sites, Youtube Videos)
Summary Of Recommender System Papers
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230
阅读过的推荐系统论文的归类总结,持续更新中…
Convncf
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107
Experimental codes for paper "Outer Product-based Neural Collaborative Filtering".
Gpufilter
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41
GPU Recursive Filtering
Bi Vae
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30
Code for the paper "Bilateral Variational Autoencoder for Collaborative Filtering", WSDM'21
Neuacf
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29
Implementation of paper Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks
Datafilter Recsys
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21
code for ResSys'18 paper: "Exploring Recommendations Under User-Controlled Data Filtering"
Acfnet
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18
This is an implementation for our paper "Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching"
Self Attentive Ncf
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15
Source code for our Paper "Self-Attentive Neural Collaborative Filtering"
Neuralchatbots Datafiltering
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11
Filter dialog data with a simple entropy-based method (see ACL paper)
Iterative Filtering Intra Prediction
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10
Code for paper "Improving Intra Prediction in High-Efficiency Video Coding"
Nllr
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9
Non-Local Low-Rank Normal Filtering for Mesh Denoising
Ldssf
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6
NIPS 2017 Paper implementation challenge Learning Linear Dynamic Systems via Spectral Filtering
Recsys2015
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6
Analysing Compression Techniques for In-Memory Collaborative Filtering
Ease Side Info Recsys 2020
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6
Source code for our LBR paper "Closed-Form Models for Collaborative Filtering with Side-Information" published at RecSys 2020.
Nonconvex Gtf Public
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6
Code for nonconvex graph trend filtering
Mrf_neurips_2019
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5
Markov Random Fields for Collaborartive Filtering
Tempered_pf
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5
Companion code for the paper "Tempered Particle Filtering"
Deep Learning For Recommendation System
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5
Deep-Learning-for-Recommendation-System
Side Window Filtering Python
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5
Python implementation of CVPR 2019 Oral paper "Side Window Filtering"
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