Sungbin Lim (임성빈)
Title
Cited by
Cited by
Year
Fast AutoAugment
S Lim, I Kim, T Kim, C Kim, S Kim
Advances in Neural Information Processing Systems 32, 6662-6672, 2019
1642019
Uncertainty-aware learning from demonstration using mixture density networks with sampling-free variance modeling
S Choi, K Lee, S Lim, S Oh
2018 IEEE International Conference on Robotics and Automation (ICRA), 6915-6922, 2018
462018
An Lq (Lp)-theory for the time fractional evolution equations with variable coefficients
I Kim, KH Kim, S Lim
Advances in Mathematics 306, 123-176, 2017
382017
Neural stain-style transfer learning using gan for histopathological images
H Cho, S Lim, G Choi, H Min
ACML Workshop on MLAIP, 2017
382017
Scalable Neural Architecture Search for 3D Medical Image Segmentation
S Kim, I Kim, S Lim, W Baek, C Kim, H Cho, B Yoon, T Kim
Medical Image Computing and Computer Assisted Intervention 22, 220-228, 2019
292019
Asymptotic behaviors of fundamental solution and its derivatives related to space-time fractional differential equations
KH Kim, S Lim
Journal of the Korean Mathematical Society 53 (4), 929-967, 2016
29*2016
Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks
S Choi, S Hong, K Lee, S Lim
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
10*2020
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning
K Lee, S Kim, S Lim, S Choi, S Oh
arXiv preprint arXiv:1902.00137, 2019
102019
Parabolic BMO estimates for pseudo-differential operators of arbitrary order
I Kim, KH Kim, S Lim
Journal of Mathematical Analysis and Applications 427 (2), 557-580, 2015
102015
An Lq(Lp)-Theory for Parabolic Pseudo-Differential Equations: Calderón-Zygmund Approach
I Kim, S Lim, KH Kim
Potential Analysis 45 (3), 463-483, 2016
92016
Parabolic Littlewood–Paley inequality for a class of time-dependent pseudo-differential operators of arbitrary order, and applications to high-order stochastic PDE
I Kim, KH Kim, S Lim
Journal of Mathematical Analysis and Applications 436 (2), 1023-1047, 2016
92016
Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds
B Kim, K Lee, S Lim, LP Kaelbling, T Lozano-Pérez
Proceedings of the AAAI Conference on Artificial Intelligence 34, 2020
82020
A Sobolev space theory for stochastic partial differential equations with time-fractional derivatives
I Kim, K Kim, S Lim
The Annals of Probability 47 (4), 2087-2139, 2019
82019
torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models
C Kim, H Lee, M Jeong, W Baek, B Yoon, I Kim, S Lim, S Kim
arXiv preprint arXiv:2004.09910, 2020
62020
Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots
K Lee, S Kim, S Lim, S Choi, M Hong, J Kim, YL Park, S Oh
Robotics: Science and Systems Foundation, 2020
22020
Supplementary Material for Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots
K Lee, S Kim, S Lim, S Choi, M Hong, J Kim, YL Park, S Oh
Technical report, Department of Electrical and Computer Engineering, Seoul …, 2020
12020
3D cell instance segmentation via point proposals using cellular components
J Choi, J Park, H Cho, H Min, S Lim, J Choo
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XIX …, 2021
2021
Neural Bootstrapper
M Shin, H Cho, S Lim
arXiv preprint arXiv:2010.01051, 2020
2020
AutoCLINT: The Winning Method in AutoCV Challenge 2019
W Baek, I Kim, S Kim, S Lim
arXiv preprint arXiv:2005.04373, 2020
2020
Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards
K Lee, H Yang, S Lim, S Oh
Advances in Neural Information Processing Systems 33, 2020
2020
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