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Hi there! ๐Ÿ‘‹

Eunhwan Park (ๆœดๆฎท็…ฅ)
Seoul, Republic of Korea.
judepark@{jbnu.ac.kr, kookmin.ac.kr}
[email protected]

I am a research engineer at Buzzni, serving my mandatory military service as Technical Research Personnel. I obtained M.S. in Computer Science from Jeonbuk National University (JBNU), where I was fortunate to be advised by Professor Seung-Hoon Na. During my M.S., I interned at NAVER Corporation, one of the biggest companies in the IT area from the Republic of Korea. Prior to JBNU, I obtained a Bachelor of Engineering in Computer Science from Kookmin University in Feb 2021, also completed of first phase certification of Software Maestro 6th from the government of the Republic of Korea in Dec 2015.

For more details, see my publications and CV.

Eunhwan Park's Projects

simple-nmt icon simple-nmt

This repo contains a simple source code for advanced neural machine translation based on sequence-to-sequence.

simpletransformers icon simpletransformers

Transformers for Classification, NER, QA, Language Modelling, Language Generation, Multi-Modal, and Conversational AI

singan icon singan

Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

snp icon snp

Sequential Neural Processes

spanbert icon spanbert

Code for using and evaluating SpanBERT.

sspvs-pytorch icon sspvs-pytorch

Pytorch implementation for "Progressive Video Summarization via Multimodal Self-supervised Learning"

tacl icon tacl

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning

tensorflow-2.x-tutorials icon tensorflow-2.x-tutorials

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0็‰ˆๅ…ฅ้—จๅฎžไพ‹ไปฃ็ ๏ผŒๅฎžๆˆ˜ๆ•™็จ‹ใ€‚

text_gcn icon text_gcn

Graph Convolutional Networks for Text Classification. AAAI 2019

tf-2.1-playground icon tf-2.1-playground

์•„ ~ ํ† ์น˜๋งŒ ํ•˜๋‹ˆ๊นŒ ๋ถˆํŽธํ•ด ~ ํ…์„œํ”Œ๋กœ์šฐ๋„ ํ•˜์ž~

tf2_course icon tf2_course

Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

tf_ner icon tf_ner

Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data

thred icon thred

The implementation of the paper "Augmenting Neural Response Generation with Context-Aware Topical Attention"

transformers icon transformers

๐Ÿค— Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

transprompt icon transprompt

This repository is implemented for our EMNLP2021 paperโ€”โ€”TransPrompt framework

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