PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

Last update: Dec 22, 2022

Overview

Recommender System in PyTorch

Implementations of various top-N recommender systems in PyTorch for practice.

Movielens 100k & 1M are used as datasets.

Available models

Model	Paper
BPRMF	Steffen Rendle et al., BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI 2009. Link
ItemKNN	Jun Wang et al., Unifying user-based and item-based collaborative filtering approaches by similarity fusion. SIGIR 2006. Link
PureSVD	Paolo Cremonesi et al., Performance of Recommender Algorithms on Top-N Recommendation Tasks. RecSys 2010. Link
SLIM	Xia Ning et al., SLIM: Sparse Linear Methods for Top-N Recommender Systems. ICDM 2011. Link
P3a	Colin Cooper et al., Random Walks in Recommender Systems: Exact Computation and Simulations. WWW 2014. Link
RP3b	Bibek Paudel et al., Updatable, accurate, diverse, and scalablerecommendations for interactive applications. TiiS 2017. Link
DAE, CDAE	Yao Wu et al., Collaborative denoising auto-encoders for top-n recommender systems. WSDM 2016.Link
MultVAE	Dawen Liang et al., Variational Autoencoders for Collaborative Filtering. WWW 2018. Link
EASE	Harald Steck, Embarrassingly Shallow Autoencoders for Sparse Data. WWW 2019. Link
NGCF	Xiang Wang, et al., Neural Graph Collaborative Filtering. SIGIR 2019. Link
LightGCN	Xiangnan He, et al., LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. SIGIR 2020. Link

Enable C++ evaluation

To evaluate with C++ backend, you have to compile C++ and cython with the following script:

python setup.py build_ext --inplace

If compiled NOT successfully, "evaluation with python backend.." will be printed in the beginning.

How to run

Edit experiment configurations in config.py
Edit model hyperparameters you choose in conf/[MODEL_NAME]
run main.py

Implement your own model

You can add your own model into the framework if:

Your model inherits BaseModel class in models/BaseModel.py
Implement necessary methods and add additional methods if you want.
Make YourModel.conf file in conf
Add your model in models.__init__

Reference

Some model implementations and util functions refers to these nice repositories.

NeuRec: An open source neural recommender library. Repository
RecSys 2019 - DeepLearning RS Evaluation. Paper Repository

PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

Related tags

Overview

Recommender System in PyTorch

Available models

Enable C++ evaluation

How to run

Implement your own model

Reference

Owner

Yoonki Jeong

3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

Perform Linear Classification with Multi-way Data

Pytorch implementation of Bert and Pals: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning

Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFlow 2

Air Quality Prediction Using LSTM

As a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).

"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022

Implementation of accepted AAAI 2021 paper: Deep Unsupervised Image Hashing by Maximizing Bit Entropy

Latex code for making neural networks diagrams

(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

PyTorch code for the ICCV'21 paper: "Always Be Dreaming: A New Approach for Class-Incremental Learning"

A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).

Deep Sketch-guided Cartoon Video Inbetweening

VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).

“英特尔创新大师杯”深度学习挑战赛赛道3：CCKS2021中文NLP地址相关性任务

Food recognition model using convolutional neural network & computer vision

StarGAN2 for practice

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Acute ischemic stroke dataset

Code of Puregaze: Purifying gaze feature for generalizable gaze estimation, AAAI 2022.

PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

Related tags

Overview

Recommender System in PyTorch

Available models

Enable C++ evaluation

How to run

Implement your own model

Reference

Owner

Yoonki Jeong

3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

Perform Linear Classification with Multi-way Data

Pytorch implementation of Bert and Pals: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning

Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFlow 2

Air Quality Prediction Using LSTM

As a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).

"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022

Implementation of accepted AAAI 2021 paper: Deep Unsupervised Image Hashing by Maximizing Bit Entropy

Latex code for making neural networks diagrams

(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

PyTorch code for the ICCV'21 paper: "Always Be Dreaming: A New Approach for Class-Incremental Learning"

A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).

Deep Sketch-guided Cartoon Video Inbetweening

VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).

“英特尔创新大师杯”深度学习挑战赛 赛道3：CCKS2021中文NLP地址相关性任务

Food recognition model using convolutional neural network & computer vision

StarGAN2 for practice

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Acute ischemic stroke dataset

Code of Puregaze: Purifying gaze feature for generalizable gaze estimation, AAAI 2022.

“英特尔创新大师杯”深度学习挑战赛赛道3：CCKS2021中文NLP地址相关性任务