Pinned Repositories
.vim
AdvCompArchPractice2022-1
align-transformers
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
BERT-pytorch
Google AI 2018 BERT pytorch implementation
BERT4Rec
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
BERT4Rec-PyTorch
graphics
MEANTIME
pl2015
Programming Language Lecture. Coq
SungMinCho's Repositories
SungMinCho/MEANTIME
SungMinCho/BERT4Rec-PyTorch
SungMinCho/AdvCompArchPractice2022-1
SungMinCho/align-transformers
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
SungMinCho/BERT-pytorch
Google AI 2018 BERT pytorch implementation
SungMinCho/BERT4Rec
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
SungMinCho/BOJ
Problem Solving at https://www.acmicpc.net/
SungMinCho/brunch-article-recommendation
SungMinCho/CartesianTreeMatching
SungMinCho/ChatCommit
SungMinCho/DeepRecSys
http://vlsiarch.eecs.harvard.edu/research/recommendation/
SungMinCho/dlrm
An implementation of a deep learning recommendation model (DLRM)
SungMinCho/EMNLP2019-NRMS
The source codes for the paper "Neural News Recommendation with Multi-Head Self-Attention".
SungMinCho/FBGEMM
FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
SungMinCho/IMDB-Scraper
Scrapy project for scraping data from IMDB with Movie Dataset including 58,623 movies' data.
SungMinCho/nodejs-practice
책 "node.js 교과서" 를 활용한 nodejs 연습
SungMinCho/othello_world
Emergent world representations: Exploring a sequence model trained on a synthetic task
SungMinCho/PaperTree
Build a tree of research paper references & Display it
SungMinCho/PGM_2022_ADNI_PLL
term project for PGM 2022
SungMinCho/PracticingScala
Practicing Scala with the red book.
SungMinCho/PyProf
A GPU performance profiling tool for PyTorch models
SungMinCho/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
SungMinCho/recsim_ng
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
SungMinCho/RecSys2019_DeepLearning_Evaluation
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"
SungMinCho/RSPapers
Must-read papers on Recommender System.
SungMinCho/SNU_2018_UROP
2018-2 UROP at SNU
SungMinCho/SR-GNN
Source code and datasets for the paper "Session-based Recommendation with Graph Neural Networks" (AAAI-19)
SungMinCho/stockAnalyze
SungMinCho/stockAnalyzeWeb
SungMinCho/tgn
TGN: Temporal Graph Networks