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, and a Student Researcher at Google Research working with Jonathan Huang. I received B.S. in Computer Science and Mathematics (double major) at KAIST.

My research focuses on video generation models that can be scaled up efficiently to real-world high-fidelity and long videos. Not limited to videos, I also have a broad interest in scaling generative models in other data domains (e.g., 3D scenes or graphs).

I was a research intern in the AI Algorithm Group at NVIDIA Research, working with wonderful mentors Weili Nie, De-An Huang, Boyi Li, and Anima Anandkumar. I always appreciate my great advisors Hongseok Yang and Juho Kim during my undergraduate study, who kindly advised me to be a conscientious researcher.

Nov 2023: Two of my papers (PVDM and NVP) won Qualcomm Innovation Fellowship Korea 2023.
Oct 2023: I will move to Kirkland to work at Google Research as a Student Researcher.
Sep 2023: GradNCP is accepted to NeurIPS 2023.
Jun 2023: I am attending CVPR in person. See you in Vancouver!
Mar 2023: I am joining NVIDIA Research as a research intern.
Feb 2023: Two papers (PVDM and AENIB) are accepted to CVPR 2023.

Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu, Younghoon Shin, Jinwoo Shin
NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development
paper

Learning Large-scale Neural Fields via Context Pruned Meta-Learning
Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin, Jonathan Richard Schwarz
NeurIPS 2023
paper  |  code

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

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

Google Research
Student Researcher (host: Jonathan Huang)
Oct 2023 - Jan 2024, Kirkland, WA

NVIDIA Research
Research Intern (mentors: Weili Nie, De-An Huang, Boyi Li, and Anima Anandkumar.)
Mar 2023 - Sep 2023, Santa Clara, CA (remote)

Google Research
University Relation Program (host: Kihyuk Sohn)
Jul 2022 - Jan 2023, Bay Area, CA (remote)

Winner, Qualcomm Innovation Fellowship Korea 2023
Recipient, CVPR 2023 Travel Awards
Recipient, CVPR 2023 Google Conference Scholarships (APAC)
Top Reviewer, NeurIPS 2022
Best Paper Awards, Korean Artificial Intelligence Association, 2021
Recipient, KAIST Presidental Fellowship
Recipient, 2019 Qualcomm-KAIST Innovation Awards
Recipient, National Presidental Scholarship for Science
Recipient, Hansung Scholarship for Gifted Students

Video Probabilistic Diffusion Models in Projected Latent Space
Jun 2023; Innerverz (remote)

Efficient Generative Models for Videos
Mar 2023; LG AI Research (Seoul, South Korea)

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)

Conference reviewer: ICML'{22,23}, NeurIPS'{22,23}, ICLR'{23,24}, CVPR'{23,24}, ICCV'23
Workshop reviewer: AI4CC@CVPR'22, Neural-Fields@ICLR'23

Teaching Assistant, Deep Learning, Fall 2020
Teaching Assistant, Samsung Electronics AI-Expert Program, Summer 2020
Peer Tutor, System Programming, Spring 2019
Teaching Assistant, Linear Algebra, Spring 2019
Teaching Assistant, Calculus 1, Spring 2018