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School of Computing, KAIST
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Presentations
(9)Likes
(10)Composing graphical models with neural networks for structured representations and fast inference
Jeongmin Cha
•
4 years ago
십분딥러닝_9_VAE(Variational Autoencoder)
HyunKyu Jeon
•
5 years ago
RLCode와 A3C 쉽고 깊게 이해하기
Woong won Lee
•
6 years ago
Waterful Application (iOS + AppleWatch)
Jeongmin Cha
•
7 years ago
데이터는 차트가 아니라 돈이 되어야 한다.
Yongho Ha
•
8 years ago
PYCON KR 2017 - 구름이 하늘의 일이라면 (윤상웅)
Haezoom Inc.
•
6 years ago
머피의 머신러닝 : Gaussian Processes
Jungkyu Lee
•
10 years ago
TensorFlow Tutorial
NamHyuk Ahn
•
7 years ago
AngularJS 2, version 1 and ReactJS
Kenneth Ceyer
•
7 years ago
객체지향 철학 그리고 5대 개념
중선 곽
•
9 years ago
Personal Information
Organization / Workplace
Gangnam-gu, Seoul, Korea Korea, South
Industry
Technology / Software / Internet
Website
www.linkedin.com/in/cjm9236
About
School of Computing, KAIST
Tags
programming
machine learning
engineering
science
computer
deep learning
presentation
system
design
software
java
javascript
python
portfolio
resume
software development
latent model
latent space
causal inference
generative model
kaist
computer science
computing
inference
graphical model
neural network
vae
additive
nonparametric
statistics
model
linear
sparsity
development
apple
app
apple watch
swift
smart watch
ios
university
hanyang
networking
embedded
microprocessor
service
maestro
network
social
sns
See more