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Sungsoo Ahn
Sungsoo Ahn
Dirección de correo verificada de postech.ac.kr - Página principal
Título
Citado por
Citado por
Año
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
6462019
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
3592020
Layer-adaptive sparsity for the magnitude-based pruning
J Lee, S Park, S Mo, S Ahn, J Shin
arXiv preprint arXiv:2010.07611, 2020
1222020
Guiding Deep Molecular Optimization with Genetic Exploration
S Ahn, J Kim, H Lee, J Shin
Advances in Neural Information Processing Systems 33, 2020
732020
Learning what to defer for maximum independent sets
S Ahn, Y Seo, J Shin
International conference on machine learning, 134-144, 2020
592020
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
322021
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
282022
Self-improved retrosynthetic planning
J Kim, S Ahn, H Lee, J Shin
International Conference on Machine Learning, 5486-5495, 2021
212021
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
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
152021
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
92021
Local search gflownets
M Kim, T Yun, E Bengio, D Zhang, Y Bengio, S Ahn, J Park
arXiv preprint arXiv:2310.02710, 2023
82023
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
Imitating graph-based planning with goal-conditioned policies
J Kim, Y Seo, S Ahn, K Son, J Shin
arXiv preprint arXiv:2303.11166, 2023
62023
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20