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2020 – today

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2024
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  - journals/tmlr/NgPLKRC24
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Nathan H. Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho:
Blind Biological Sequence Denoising with Self-Supervised Set Learning. Trans. Mach. Learn. Res. 2024 (2024)
2023
[j1]
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  - journals/bioinformatics/RiahiLSWJOZPWMQ23
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Saleh Riahi, Jae Hyeon Lee, Taylor Sorenson, Shuai Wei, Sven Jager, Reza Olfati-Saber, Yanfeng Zhou, Anna Park, Maria Wendt, Hervé Minoux, Yu Qiu:
Surface ID: a geometry-aware system for protein molecular surface comparison. Bioinform. 39(4) (2023)
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  - journals/corr/abs-2302-07754
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Michael Maser, Ji Won Park, Joshua Yao-Yu Lin, Jae Hyeon Lee, Nathan C. Frey, Andrew M. Watkins:
SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers. CoRR abs/2302.07754 (2023)
[i4]
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  - journals/corr/abs-2304-02291
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Jae Hyeon Lee, Chang-Hwan Son:
Trap-Based Pest Counting: Multiscale and Deformable Attention CenterNet Integrating Internal LR and HR Joint Feature Learning. CoRR abs/2304.02291 (2023)
[i3]
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  - journals/corr/abs-2306-11681
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Michael Maser, Natasa Tagasovska, Jae Hyeon Lee, Andrew M. Watkins:
MoleCLUEs: Optimizing Molecular Conformers by Minimization of Differentiable Uncertainty. CoRR abs/2306.11681 (2023)
[i2]
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  - journals/corr/abs-2309-01670
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Nathan Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho:
Blind Biological Sequence Denoising with Self-Supervised Set Learning. CoRR abs/2309.01670 (2023)
2022
[i1]
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  - journals/corr/abs-2205-04259
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Daniel Berenberg, Jae Hyeon Lee, Simon Kelow, Ji Won Park, Andrew M. Watkins, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho:
Multi-segment preserving sampling for deep manifold sampler. CoRR abs/2205.04259 (2022)

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