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MikroKosmos
- San Francisco
- https://www.linkedin.com/in/messi-ki-20b3a4172/
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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
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"
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
A Python implementation of LightFM, a hybrid recommendation algorithm.
Code for the paper "Stochastic Variational Inference for Dynamic Correlated Topic Models"
This repository implements variational graph auto encoder by Thomas Kipf.