Code for the paper "On First-Order Meta-Learning Algorithms"

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

2019 KAIST 딥러닝 홀로서기 세미나용 저장소입니다.

Workshop on Bayesian inference using PyMC

matrix factorization in PyTorch

Python and Cython implementation of state-of-the-art collaborative filtering models.

Implementation of the RecWalk recommendation algorithm

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

구글 빅쿼리 완벽 가이드

Matrix factorization models with social tags for music recommendation.

꼼꼼한 딥러닝 논문 리뷰와 코드 실습

Variational autoencoders for collaborative filtering

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

PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Chinese Restaurant Process Clustering in Julia and Python

allRank is a framework for training learning-to-rank neural models based on PyTorch.

Graph Convolutional Matrix Completion for Implicit Feedback

A library of metrics for evaluating recommender systems

Regularizing Matrix Factorization with User and Item Embeddings for Recommendation -- CIKM 2018

그래프 딥러닝 라이브러리 DGL 쉽게 배우기

A Python implementation of LightFM, a hybrid recommendation algorithm.

Python package of Tomoto, the Topic Modeling Tool

Code for the paper "Stochastic Variational Inference for Dynamic Correlated Topic Models"

This repository implements variational graph auto encoder by Thomas Kipf.

Deep recommender models using PyTorch.