An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

Overview

DOI

An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

This repository was developed by Fernando B. Pérez Maurera. Fernando is a Ph.D. student at Politecnico di Milano.

This repository contains the source code of the following articles:

  • An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering. Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, and Paolo Cremonesi. Accepted to ECIR 2022.

See our website for more information on our research group. We are actively pursuing this research direction in evaluation and reproducibility, we are open to collaboration with other researchers. Follow our project on ResearchGate

This repo is divided in three folders:

You'll find instructions to install this project and run the experiments in the
README inside evaluation-cfgan, in fact, all commands must be run inside the evaluation-cfgan folder.

You might also like...
Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch
Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch

alias-free-gan-pytorch Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) This implementation

PyTorch implementations of Generative Adversarial Networks.
PyTorch implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Image Deblurring using Generative Adversarial Networks
Image Deblurring using Generative Adversarial Networks

DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo

Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

StackGAN-v2 StackGAN-v1: Tensorflow implementation StackGAN-v1: Pytorch implementation Inception score evaluation Pytorch implementation for reproduci

Code for
Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks"

Note: this repo has been discontinued, please check code for newer version of the paper here Weight Normalized GAN Code for the paper "On the Effects

PyTorch implementation of
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

DiscoGAN in PyTorch PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. * All samples in READM

Official implementation of
Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

DiscoGAN Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. Prerequisites Python 2.7

Releases(v1.1.1-ecir-2022-camera-ready)
Owner
Fernando Benjamín PÉREZ MAURERA
Computer Engineer & Ph.D. candidate in Information Technology
Fernando Benjamín PÉREZ MAURERA
Code for One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning (AAAI 2022)

One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning (AAAI 2022) Paper | Demo Requirements Python = 3.6 , Pytorch

FuxiVirtualHuman 84 Jan 03, 2023
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks

FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks Image Classification Dataset: Google Landmark, COCO, ImageNet Model: Efficient

FedML-AI 62 Dec 10, 2022
Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.

CLIP-Guided-Diffusion Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. Original colab notebooks by Ka

Nerdy Rodent 336 Dec 09, 2022
Evaluating Cross-lingual Sentence Representations

XNLI: The Cross-Lingual NLI Corpus XNLI is an evaluation corpus for language transfer and cross-lingual sentence classification in 15 languages. New:

Meta Research 395 Dec 19, 2022
Realtime segmentation with ENet, the fast and accurate segmentation net.

Enet This is a realtime segmentation net with almost 22 fps on GTX1080 ti, and the model size is very small with only 28M. This repo contains the infe

JinTian 14 Aug 30, 2022
code for Fast Point Cloud Registration with Optimal Transport

robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the

28 Jan 04, 2023
Implementation of U-Net and SegNet for building segmentation

Specialized project Created by Katrine Nguyen and Martin Wangen-Eriksen as a part of our specialized project at Norwegian University of Science and Te

Martin.w-e 3 Dec 07, 2022
SW components and demos for visual kinship recognition. An emphasis is put on the FIW dataset-- data loaders, benchmarks, results in summary.

FIW Data Development Kit Table of Contents Introduction Families In the Wild Database Publications Organization To Do License Getting Involved Introdu

Joseph P. Robinson 12 Jun 04, 2022
PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambiguation for Partial Label Learning

PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambig

王皓波 147 Jan 07, 2023
Semi-automated OpenVINO benchmark_app with variable parameters

Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of gi

Yasunori Shimura 8 Apr 11, 2022
Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

kenro515 3 Jan 04, 2023
Object Detection using YOLO from PyImageSearch

Object Detection using YOLO from PyImageSearch By applying object detection, you’ll not only be able to determine what is in an image, but also where

Mohamed NIANG 1 Feb 09, 2022
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning"

PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning".

Berivan Isik 8 Dec 08, 2022
Ranger deep learning optimizer rewrite to use newest components

Ranger21 - integrating the latest deep learning components into a single optimizer Ranger deep learning optimizer rewrite to use newest components Ran

Less Wright 266 Dec 28, 2022
yolov5目标检测模型的知识蒸馏(基于响应的蒸馏)

代码地址: https://github.com/Sharpiless/yolov5-knowledge-distillation 教师模型: python train.py --weights weights/yolov5m.pt \ --cfg models/yolov5m.ya

52 Dec 04, 2022
[CIKM 2021] Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning

Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning. This repo contains the PyTorch code and implementation for the paper E

Akuchi 18 Dec 22, 2022
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)

A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G

Ching-Yao Chuang 427 Dec 13, 2022
Unofficial PyTorch Implementation of AHDRNet (CVPR 2019)

AHDRNet-PyTorch This is the PyTorch implementation of Attention-guided Network for Ghost-free High Dynamic Range Imaging (CVPR 2019). The official cod

Yutong Zhang 4 Sep 08, 2022
Bottom-up Human Pose Estimation

Introduction This is the official code of Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation. This paper has been accepted to CVPR2

108 Dec 01, 2022
I decide to sync up this repo and self-critical.pytorch. (The old master is in old master branch for archive)

An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin

Ruotian(RT) Luo 1.3k Dec 31, 2022