seonghyun26
PhD in Machine Learning for Molecules Lab @ KAIST AI, advised by Sungsoo Ahn
KAIST AISeoul
Pinned Repositories
2020_poapper_hackaton
포애퍼 해카톤 2020
2020_UGRP
Personal Mobility Tracking Device
22UMLProject
2022 UML Project at INSA Lyon
332project
anomaly_detection
bgflow
goat
GOAl conditioned Transition path sampling (TPS)
hanjun_2021
Electric-Car-Optimization System
nba-gnn
pintos
seonghyun26's Repositories
seonghyun26/2020_UGRP
Personal Mobility Tracking Device
seonghyun26/hanjun_2021
Electric-Car-Optimization System
seonghyun26/pintos
seonghyun26/2020_poapper_hackaton
포애퍼 해카톤 2020
seonghyun26/22UMLProject
2022 UML Project at INSA Lyon
seonghyun26/caffe
Caffe: a fast open framework for deep learning.
seonghyun26/FS-Mol
FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.
seonghyun26/Graphormer
Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material design, drug discovery, etc.
seonghyun26/Hello_World
test
seonghyun26/MELD
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation
seonghyun26/pintos-1
Pintos project in KAIST
seonghyun26/reactjs_movie
Nomad React JS Movie Web Service
seonghyun26/tp-insa-anonymity
2022 INSA Lyon Database Course
seonghyun26/typechain
Learning Typescript