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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.
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News
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.
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Research
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.
Learning Large-scale Neural Fields via Context Pruned Meta-Learning
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
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
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Work Experience
NVIDIA Research
Research Intern, hosted by Weili Nie (Mar 2023 - present)
Google Research
Google University Relations, hosted by Kihyuk Sohn (Jul 2022 - present)
NAVER AI Lab
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)
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Honors and Awards
Recipient, Google Conference Scholarships (APAC), CVPR 2023
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
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Invited Talks
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)
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Academic Services
Conference reviewer: ICML'{22,23}, NeurIPS'{22,23}, ICLR'23, CVPR'23, ICCV'23
Workshop reviewer: AI4CC@CVPR'22, Neural-Fields@ICLR'23
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Teaching
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
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