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2020 – today
- 2024
[j2]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]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) - [i5]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]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]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]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]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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