Jihoon Tack

I am a Ph.D. student at KAIST, advised by Prof. Jinwoo Shin, and a visiting Ph.D student at University of Oxford, advised by Prof. Yee Whye Teh. I also work closely with Jonathan Richard Schwarz at DeepMind and Prof. Jaeho Lee at POSTECH. My recent research interests focus on meta-learning algorithm design and its applications for neural fields (also referred to as implicit neural representations). I also have interests in developing robust representation learning frameworks.

Topics of interest (publications with overlap):

• Meta-Learning: arXiv'23, ICML'23, ICLR'23, NeurIPS'22, NeurIPS'21
• Neural Field / Implicit Neural Representation: arXiv'23, ICML'23, ICLR'22, NeurIPS'21
• Distributional Shift Robustness: SaTML'23, AAAI'22, NeurIPS'20a, NeurIPS'20b

(C: Conference, W: Workshop, P: Preprint, *: Equal contribution)

[W2] Learning Large-scale Neural Fields via Context Pruned Meta-Learning

Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin, Jonathan Richard Schwarz
ICLR Workshop on Neural Fields (ICLRW-NF) 2023
paper | code

[C10] Modality-Agnostic Variational Compression of Implicit Neural Representations

Jihoon Tack*, Jonathan Richard Schwarz*, Yee Whye Teh, Jaeho Lee, Jinwoo Shin
International Conference on Machine Learning (ICML) 2023
ICLR Workshop on Neural Fields (ICLRW-NF) 2023
paper

[C9] STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin
International Conference on Learning Representations (ICLR) 2023, Spotlight presentation
NeurIPS Workshop on Table Representation Learning (NeurIPSW-TRL) 2022
Bronze Prize, Samsung Humantech Paper Awards 2023
paper | code

[C8] Rethinking the Entropy of Instance in Adversarial Training

Minseon Kim, Jihoon Tack, Jinwoo Shin, Sung Ju Hwang
IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) 2023
ICML Workshop on Adversarial Machine Learning (ICMLW-AdvML) 2021
paper

[C7] Meta-Learning with Self-Improving Momentum Target

Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin
Conference on Neural Information Processing Systems (NeurIPS) 2022
paper | code | slide | poster

[C6] K-centered Patch Sampling for Efficient Video Recognition

Seong Hyeon Park, Jihoon Tack, Byeongho Heo, Jung-Woo Ha, Jinwoo Shin
European Conference on Computer Vision (ECCV) 2022
paper | code

[C5] Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks

Sihyun Yu*, Jihoon Tack*, Sangwoo Mo*, Hyunsu Kim, Junho Kim, Jung-Woo Ha,
Jinwoo Shin
International Conference on Learning Representations (ICLR) 2022
CVPR Workshop on AI for Content Creation (CVPRW-AI4CC) 2022
paper | code | slide | project page

[C4] Consistency Regularization for Adversarial Robustness

Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, Jinwoo Shin
AAAI Conference on Artificial Intelligence (AAAI) 2022
ICML Workshop on Adversarial Machine Learning (ICMLW-AdvML) 2021, Oral presentation
paper | code | slide | poster

[C3] Meta-Learning Sparse Implicit Neural Representations

Jihoon Tack*, Jaeho Lee*, Namhoon Lee, Jinwoo Shin
Conference on Neural Information Processing Systems (NeurIPS) 2021
Sparsity in Neural Networks Workshop (SNN) 2021
paper | code | slide | poster

[C2] CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances

Jihoon Tack*, Sangwoo Mo*, Jongheon Jeong, Jinwoo Shin
Conference on Neural Information Processing Systems (NeurIPS) 2020
Qualcomm Innovation Fellowship Korea 2020
paper | code | slide | poster

[C1] Adversarial Self-Supervised Contrastive Learning

Minseon Kim, Jihoon Tack, Sung Ju Hwang
Conference on Neural Information Processing Systems (NeurIPS) 2020
paper | code | project page

[W1] Consistency Regularization for Training Confidence-Calibrated Classifiers

Youngbum Hur*, Jihoon Tack*, Eunho Yang, Sung Ju Hwang, Jinwoo Shin
ICML Workshop on Uncertainty & Robustness in Deep Learning (ICMLW-UDL) 2021
paper

• M.S. & Ph.D. in Artificial Intelligence
  Korea Advanced Institute of Science and Technology (KAIST), Mar. 2019 - present
  Advisor: Prof. Jinwoo Shin
• B.S. in Electrical Engineering and Mathematics (minored)
  Korea Advanced Institute of Science and Technology (KAIST), Mar. 2014 - Feb. 2019

• Visiting Student, University of Oxford, Working with Prof. Yee Whye Teh, Jun. 2023 - Dec. 2023

• Bronze Prize, Samsung Humantech Paper Awards 2023
• Top Reviewer Award (top 10%), NeurIPS 2022
• Best Paper Award, Korean Artificial Intelligence Association 2021
• Outstanding Reviewer Award, CVPR 2021
• Winner, Qualcomm Innovation Fellowship Korea 2020
• Top Reviewer Award (top 10%), NeurIPS 2020

• Conference Reviewer: NeurIPS, ICML, ICLR, CVPR, ICCV, AAAI
• Journal Reviewer: TMLR, IJCV, IEEE TNNLS, IEEE TIFS, IEEE TIP