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Sihyun Yu

sihyun.yu at kaist dot ac dot kr
yusihyunc at gmail dot com


I am a Ph.D. student at KAIST, advised by Jinwoo Shin. I also work closely with Kihyuk Sohn, who is at Google Research. Prior to this, I received B.S. in Computer Science and Mathematics (double major) at KAIST under the supervision of Hongseok Yang and Juho Kim, who kindly advised me to be a conscientious researcher.

Currently, I am a research intern at NVIDIA Research, working with wonderful mentors Weili Nie, Zhiding Yu, De-An Huang, Boyi Li, and Anima Anandkumar.


Mar 2023: I am joining NVIDIA Research as a research intern.
Mar 2023: ECoP is accepted to ICLR 2023 Workshop on Neural Fields across Fields.
Feb 2023: Two papers (PVDM and AENIB) are accepted to CVPR 2023.
Nov 2022: I will attend NeurIPS 2022 offline.
Sep 2022: NVP is accepted to NeurIPS 2022.


My research lies in making deep generative models scalable towards real-world high-dimensional data and their deployment to real-world scenarios. To achieve this goal, I usually focus on alleviating huge memory burdens or computations of deep generative models. Currently, I am mainly working in video synthesis, but not limited to; other complex data (e.g., 3D scenes and graphs), and any other applications are also in my broad interest. Besides, I also have an interest in the robustness of neural networks to the distributional shift.

Efficient Meta-Learning via Error-based Context Pruning for Implicit Neural Representations
Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin, Jonathan Richard Schwarz
ICLR 2023 Workshop on Neural Fields across Fields.
paper  |  code

Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck
Jongheon Jeong, Sihyun Yu, Hankook Lee, Jinwoo Shin
CVPR 2023

Video Probabilistic Diffusion Models in Projected Latent Space
Sihyun Yu, Kihyuk Sohn, Subin Kim, Jinwoo Shin
CVPR 2023
paper  |  project page  |  code

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

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  |  slide  |  code

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

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

Work Experience

NVIDIA Research
Research Intern, hosted by Weili Nie (Feb 2023 - Sep 2023; expected)

Google Research
Google University Relations, hosted by Kihyuk Sohn (Jul 2022 - present)

External Collaborator, hosted by Jung-Woo Ha (Jun 2021 - Sep 2021)

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
External Collaborator, hosted by Le Song and Sungsoo Ahn (Mar 2021 - May 2021)

Korea Advanced Institute of Science and Technology (KAIST)
Research Intern, hosted by Hongseok Yang (April 2018 - June 2019)

Honors and Awards

Top Reviewer, NeurIPS 2022
Best Paper Awards, Korean Artificial Intelligence Association, 2021
Recipient, KAIST Presidental Fellowship, 2018-2020
Recipient, Qualcomm-KAIST Innovation Awards, 2019
Recipient, National Presidental Scholarship for Science, 2017-2020
Recipient, Hansung Scholarship for Gifted Students, 2015-2016

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)

Academic Services

Conference reviewer: ICML'{22,23}, NeurIPS'22, ICLR'23, CVPR'23, ICCV'23
Workshop reviewer: AI4CC@CVPR'22, Neural-Fields@ICLR'23


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