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Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost


Oct 27, 2022
Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong

* 19 pages, 8 figures 

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Equivariant Hypergraph Neural Networks


Aug 22, 2022
Jinwoo Kim, Saeyoon Oh, Sungjun Cho, Seunghoon Hong

* 29 pages, 2 figures 

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Diverse Generative Adversarial Perturbations on Attention Space for Transferable Adversarial Attacks


Aug 11, 2022
Woo Jae Kim, Seunghoon Hong, Sung-Eui Yoon

* ICIP 2022 

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Pure Transformers are Powerful Graph Learners


Jul 06, 2022
Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong

* 26 pages, 8 figures 

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Part-based Pseudo Label Refinement for Unsupervised Person Re-identification


Mar 28, 2022
Yoonki Cho, Woo Jae Kim, Seunghoon Hong, Sung-Eui Yoon

* CVPR 2022 

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Learning to Generate Novel Classes for Deep Metric Learning


Jan 04, 2022
Kyungmoon Lee, Sungyeon Kim, Seunghoon Hong, Suha Kwak

* Accepted to BMVC 2021 

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Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution


Oct 30, 2021
Jaechang Kim, Yunjoo Lee, Seunghoon Hong, Jungseul Ok

* submitted to ICASSP 2022 

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Multi-Task Processes


Oct 29, 2021
Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong

* 33 pages, 13 figures 

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Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs


Oct 27, 2021
Jinwoo Kim, Saeyoon Oh, Seunghoon Hong

* 21 pages, 5 figures 

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Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction


Apr 14, 2021
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong

* Accepted as a conference paper at ICLR 2021 

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