Sihyun Yu

I am a Ph.D. student at Algorithmic Intelligence Laboratory @ KAIST, advised by professor Jinwoo Shin.

Prior to this, I received B.S. in Computer Science and Mathematics (double major) at KAIST, and I did my research about physics-inspired distribution sampling methods under the supervision of professor Hongseok Yang.

Email | CV | Google Scholar | Twitter | Github

Research

My research focuses on designing deep generative models of videos and 3D scenes. Specifically, I am focusing on discovering priors that would enable the effective synthesis of these data. I also have an interest in adversarial robustness.

2022

Scalable Neural Video Representations with Learnable Positional Features
Subin Kim*, Sihyun Yu*, Jaeho Lee, Jinwoo Shin
NeurIPS 2022
project page

Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
Sihyun Yu*, Jihoon Tack*, Sangwoo Mo*, Hyunsu Kim, Junho Kim, Jung-Woo Ha, Jinwoo Shin
ICLR 2022
paper | project page | slides | code

Consistency Regularization for Adversarial Robustness
Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, Jinwoo Shin
AAAI 2022
paper | slides | code

Learning Robust Representations via Nuisance-extended Information Bottleneck
Jongheon Jeong, Sihyun Yu, Hankook Lee, Jinwoo Shin
ECCV 2022 Workshop on Out of Distribution Generalization in Computer Vision (OOD-CV)
paper

2021

RoMA: Robust Model Adaptation for Offline Model-based Optimization
Sihyun Yu, Sungsoo Ahn, Le Song, Jinwoo Shin
NeurIPS 2021
paper | slides | code

Abstract Reasoning via Logic-guided Generation
Sihyun Yu, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin
ICML 2021 Workshop on Self-Supervised Learning for Reasoning and Perception (oral)
paper | slides | poster

Invited Talks

RoMA: Robust Model Adaptation for Offline Model-based Optimization
Jun 2022; Samsung Electronics (Suwon, South Korea)

Scaling Video Generation via Implicit Neural Representations
Jun 2022; Pohang University of Science and Technology (Pohang, South Korea)

Abstract Reasoning via Logic-guided Generation
Jun 2021; ICML Workshop on Self-Supervised Learning for Reasoning and Perception 2021 (remote)

Collaborations

Google Research
with Dr. Kihyuk Sohn as an external collaborator (Jul 2022 - present)

NAVER AI Lab
with Dr. Jung-Woo Ha as an external collaborator (Jun 2021 - Sep 2021)

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
with Prof. Le Song and Prof. Sungsoo Ahn as an external collaborator (Mar 2021 - May 2021)

Korea Advanced Institute of Science and Technology (KAIST)
with Prof. Hongseok Yang (April 2018 - June 2019)

Academic Services

Conference reviewer: ICML 2022, NeurIPS 2022

Workshop reviewer: CVPRW (AI4CC) 2022

Selective Honors

Best Paper Awards, Korean Artificial Intelligence Association, 2021
Qualcomm-KAIST Innovation Awards, 2019
KAIST Presidental Fellowship, 2018-2020
National Presidental Scholarship for Science, 2017-2020
Hansung Scholarship for Gifted Students, 2015-2016

Teaching

TA, Deep Learning (AI502), Fall 2020
TA, Samsung Electronics Device Solutions, AI-Expert Program, Summer 2020
Peer Tutor, System Programming (CS230), Spring 2019
TA, Linear Algebra (MAS212), Spring 2019
TA, Calculus 1 (MAS101), Spring 2018

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