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Juho Lee
Juho Lee
Associate professor, KAIST
Verified email at kaist.ac.kr - Homepage
Title
Cited by
Cited by
Year
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
J Lee, Y Lee, J Kim, A Kosiorek, S Choi, YW Teh
International Conference on Machine Learning, 3744-3753, 2019
13572019
Learning to propagate labels: Transductive propagation network for few-shot learning
Y Liu, J Lee, M Park, S Kim, E Yang, SJ Hwang, Y Yang
arXiv preprint arXiv:1805.10002, 2018
9282018
Adversarial purification with score-based generative models
J Yoon, SJ Hwang, J Lee
International Conference on Machine Learning, 12062-12072, 2021
1592021
Uncertainty-aware attention for reliable interpretation and prediction
J Heo, HB Lee, S Kim, J Lee, KJ Kim, E Yang, SJ Hwang
Advances in neural information processing systems 31, 2018
1052018
Setvae: Learning hierarchical composition for generative modeling of set-structured data
J Kim, J Yoo, J Lee, S Hong
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
852021
Bootstrapping neural processes
J Lee, Y Lee, J Kim, E Yang, SJ Hwang, YW Teh
Advances in neural information processing systems 33, 6606-6615, 2020
492020
Diversity matters when learning from ensembles
G Nam, J Yoon, Y Lee, J Lee
Advances in neural information processing systems 34, 8367-8377, 2021
432021
A multi-mode modulator for multi-domain few-shot classification
Y Liu, J Lee, L Zhu, L Chen, H Shi, Y Yang
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
422021
Towards safe self-distillation of internet-scale text-to-image diffusion models
S Kim, S Jung, B Kim, M Choi, J Shin, J Lee
arXiv preprint arXiv:2307.05977, 2023
242023
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models
J Lee, LF James, S Choi
Advances in Neural Information Processing Systems, 2016
202016
Learning to perturb word embeddings for out-of-distribution QA
S Lee, M Kang, J Lee, SJ Hwang
arXiv preprint arXiv:2105.02692, 2021
192021
Probabilistic imputation for time-series classification with missing data
SH Kim, H Kim, E Yun, H Lee, J Lee, J Lee
International Conference on Machine Learning, 16654-16667, 2023
182023
DropMax: Adaptive variational softmax
HB Lee, J Lee, S Kim, E Yang, SJ Hwang
Advances in Neural Information Processing Systems 31, 2018
18*2018
Online video segmentation by bayesian split-merge clustering
J Lee, S Kwak, B Han, S Choi
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
182012
Deep amortized clustering
J Lee, Y Lee, YW Teh
arXiv preprint arXiv:1909.13433, 2019
172019
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior
F Ayed, J Lee, F Caron
International Conference on Machine Learning, 2019
162019
Deep mixed effect model using Gaussian processes: a personalized and reliable prediction for healthcare
I Chung, S Kim, J Lee, KJ Kim, SJ Hwang, E Yang
Proceedings of the AAAI conference on artificial intelligence 34 (04), 3649-3657, 2020
132020
Decoupled training for long-tailed classification with stochastic representations
G Nam, S Jang, J Lee
arXiv preprint arXiv:2304.09426, 2023
122023
Exploring the role of mean teachers in self-supervised masked auto-encoders
Y Lee, J Willette, J Kim, J Lee, SJ Hwang
arXiv preprint arXiv:2210.02077, 2022
122022
On divergence measures for bayesian pseudocoresets
B Kim, J Choi, S Lee, Y Lee, JW Ha, J Lee
Advances in Neural Information Processing Systems 35, 757-767, 2022
112022
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