Name: Maurizio Ferrari Dacrema
Type: User
Company: Politecnico di Milano
Bio: Assistant Professor, recommender systems evaluation and applied quantum machine learning. Twitter @Maurizio_fd
Twitter: Maurizio_fd
Location: Milano, Italy
Blog: https://mauriziofd.github.io/
Maurizio Ferrari Dacrema's Projects
Code for "Collaborative Filtering with User-Item Co-Autoregressive Models"
HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-start Recommendation
Low-Rank Linear Autoencoder, LLAE, AAAI 2019, From Zero-Shot Learning to Cold-Start Recommendation
Source code and datasets for the paper "Session-based Recommendation with Graph Neural Networks" (AAAI-19)
Reasoning Over Knowledge Graph Paths for Recommendation
This repository contains the core model we called "Collaborative filtering enhanced Content-based Filtering" published in our UMUAI article "Movie Genome: Alleviating New Item Cold Start in Movie Recommendation"
Attentional Content & Collaborate Model
Update U efficiently
code for our paper Neural Collaborative Ranking
A tensorflow implementation of RippleNet
Regularizing Matrix Factorization with User and Item Embeddings for Recommendation -- CIKM 2018
The implementation of "Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence"
Simple HTML/CSS website template for a small academic/tech conference
A developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks
Google Research
Part of codes for A Knowledge-Enhanced Deep Recommendation Framework Incorporating GAN-based Models
Code For Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention
A implementation of CF-NADE. Yin Zheng, et. al. "A Neural Autoregressive Approach to Collaborative Filtering", accepted by ICML 2016.
Attentive Contextual Denoising Autoencoder
Experimental codes for paper "Outer Product-based Neural Collaborative Filtering".
The paper and code of CoupledCF in Ijcai 2018