*: equal contribution, †: equal advising
Architecture-Agnostic Invariances for Deep Learning
Jinwoo Kim
Ph.D. Dissertation, 2026. KAIST CoE Best Dissertation Award
[pdf]
Inverting Data Transformations via Diffusion Sampling
Jinwoo Kim*, Sékou-Oumar Kaba*, Jiyun Park, Seunghoon Hong†, Siamak
Ravanbakhsh†
Under review, 2026
Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
Jinwoo Kim*, Xingyue Huang*, Krzysztof Olejniczak, Kyungbin Min, Michael Bronstein, Seunghoon Hong, İsmail
İlkan
Ceylan
ICLR, 2026
[paper] [code]
Sequence Modeling with Spectral Mean Flows
Jinwoo Kim, Max Beier, Petar Bevanda, Nayun Kim, Seunghoon Hong
NeurIPS, 2025
[paper] [code]
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim, Olga Zaghen*, Ayhan Suleymanzade*, Youngmin Ryou, Seunghoon Hong
ICLR, 2025. Spotlight (380/11672=3.26%)
ICML GRaM Workshop, 2024. ELLIS Mobility Grant
[paper] [code]
[poster]
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation
Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae
Lee
AAAI, 2025. Oral
[paper]
Simulation-Free Training of Neural ODEs on Paired Data
Semin Kim*, Jaehoon Yoo*, Jinwoo Kim, Yeonwoo Cha, Saehoon Kim, Seunghoon Hong
NeurIPS, 2024
[paper] [code]
Learning Symmetrization for Equivariance with Orbit Distance Minimization
Tien Dat Nguyen*, Jinwoo Kim*, Hongseok Yang, Seunghoon Hong
NeurIPS NeurReps Workshop, 2023
[paper] [code] [poster]
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
Jinwoo Kim, Tien Dat Nguyen, Ayhan Suleymanzade, Hyeokjun An, Seunghoon Hong
NeurIPS, 2023. Spotlight (378/12345=3.06%)
[paper] [code] [poster] [slides]
[extended
slides]
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching
Donggyun Kim, Jinwoo Kim, Seongwoong Cho, Chong Luo, Seunghoon Hong
ICLR, 2023. Outstanding Paper Award (4/4955=0.08%)
Silver Prize, Samsung Humantech Paper Award, 2023
[paper] [code]
Pure Transformers are Powerful Graph Learners
Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee†, Seunghoon
Hong†
NeurIPS, 2022
[paper] [code] [talk] [poster] [slides]
[extended
slides]
Transformers Meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost
Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
NeurIPS, 2022
[paper] [code]
[poster]
Equivariant Hypergraph Neural Networks
Jinwoo Kim, Saeyoon Oh, Sungjun Cho, Seunghoon Hong
ECCV, 2022
[paper] [code] [poster] [slides]
Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs
Jinwoo Kim, Saeyoon Oh, Seunghoon Hong
NeurIPS, 2021
Qualcomm Innovation Fellowship Korea, 2021
[paper] [code] [poster] [slides]
SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data
Jinwoo Kim*, Jaehoon Yoo*, Juho Lee, Seunghoon Hong
CVPR, 2021
[paper] [code] [project] [poster] [slides]
Spontaneous Retinal Waves Can Generate Long-Range Horizontal Connectivity in Visual Cortex
Jinwoo Kim*, Min Song*, Jaeson Jang, Se-Bum Paik
The Journal of Neuroscience 40(34), 2020
[paper]