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Sungsoo Ahn
Sungsoo Ahn
postech.ac.kr의 이메일 확인됨 - 홈페이지
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Variational information distillation for knowledge transfer
S Ahn, SX Hu, A Damianou, ND Lawrence, Z Dai
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
6432019
Learning from Failure: De-biasing Classifier from Biased Classifier
J Nam, H Cha, S Ahn, J Lee, J Shin
Advances in Neural Information Processing Systems 33, 2020
3512020
Layer-adaptive sparsity for the magnitude-based pruning
J Lee, S Park, S Mo, S Ahn, J Shin
arXiv preprint arXiv:2010.07611, 2020
1182020
Guiding Deep Molecular Optimization with Genetic Exploration
S Ahn, J Kim, H Lee, J Shin
Advances in Neural Information Processing Systems 33, 2020
722020
Learning what to defer for maximum independent sets
S Ahn, Y Seo, J Shin
International conference on machine learning, 134-144, 2020
582020
Roma: Robust model adaptation for offline model-based optimization
S Yu, S Ahn, L Song, J Shin
Advances in Neural Information Processing Systems 34, 4619-4631, 2021
302021
Learning debiased classifier with biased committee
N Kim, S Hwang, S Ahn, J Park, S Kwak
Advances in Neural Information Processing Systems 35, 18403-18415, 2022
262022
A closer look at the intervention procedure of concept bottleneck models
S Shin, Y Jo, S Ahn, N Lee
International Conference on Machine Learning, 31504-31520, 2023
202023
Self-improved retrosynthetic planning
J Kim, S Ahn, H Lee, J Shin
International Conference on Machine Learning, 5486-5495, 2021
192021
Spanning tree-based graph generation for molecules
S Ahn, B Chen, T Wang, L Song
International Conference on Learning Representations, 2021
182021
QTRAN++: improved value transformation for cooperative multi-agent reinforcement learning
K Son, S Ahn, RD Reyes, J Shin, Y Yi
arXiv preprint arXiv:2006.12010, 2020
182020
RetCL: a selection-based approach for retrosynthesis via contrastive learning
H Lee, S Ahn, SW Seo, YY Song, E Yang, SJ Hwang, J Shin
arXiv preprint arXiv:2105.00795, 2021
142021
Sythesis of MCMC and Belief Propagation
S Ahn, M Chertkov, J Shin
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2016
132016
What makes better augmentation strategies? augment difficult but not too different
J Kim, D Kang, S Ahn, J Shin
International Conference on Learning Representations, 2021
82021
Abstract reasoning via logic-guided generation
S Yu, S Mo, S Ahn, J Shin
arXiv preprint arXiv:2107.10493, 2021
82021
Minimum weight perfect matching via blossom belief propagation
S Ahn, S Park, M Chertkov, J Shin
Advances in Neural Information Processing Systems, 1288-1296, 2015
82015
Gauging variational inference
S Ahn, M Chertkov, J Shin
Advances in Neural Information Processing Systems, 2881-2890, 2017
72017
Fragment-based multi-view molecular contrastive learning
S Kim, J Nam, J Kim, H Lee, S Ahn, J Shin
Workshop on''Machine Learning for Materials''ICLR 2023, 2023
62023
A deeper look at the layerwise sparsity of magnitude-based pruning
J Lee, S Park, S Mo, S Ahn, J Shin
arXiv preprint arXiv:2010.07611 2 (3), 2020
62020
Gauged mini-bucket elimination for approximate inference
S Ahn, M Chertkov, J Shin, A Weller
International Conference on Artificial Intelligence and Statistics, 10-19, 2018
62018
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학술자료 1–20