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Stefanie Jegelka
Stefanie Jegelka
TUM and MIT
在 mit.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
How powerful are graph neural networks?
K Xu, W Hu, J Leskovec, S Jegelka
arXiv preprint arXiv:1810.00826, 2018
78592018
Representation learning on graphs with jumping knowledge networks
K Xu, C Li, Y Tian, T Sonobe, K Kawarabayashi, S Jegelka
International Conference on Machine Learning, 5453-5462, 2018
21012018
Deep metric learning via lifted structured feature embedding
H Oh Song, Y Xiang, S Jegelka, S Savarese
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
19282016
Contrastive learning with hard negative samples
J Robinson, SJ Chuang, Ching-Yao, Suvrit Sra
International Conference on Learning Representations, 2021
6912021
Debiased contrastive learning
CY Chuang, J Robinson, YC Lin, A Torralba, S Jegelka
Advances in Neural Information Processing Systems 33, 2020
5592020
Max-value entropy search for efficient Bayesian optimization
Z Wang, S Jegelka
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
4602017
Deep Metric Learning via Facility Location
HO Song, S Jegelka, V Rathod, K Murphy
CVPR, 2017
3722017
How neural networks extrapolate: From feedforward to graph neural networks
K Xu, M Zhang, J Li, SS Du, K Kawarabayashi, S Jegelka
arXiv preprint arXiv:2009.11848, 2020
3162020
Generalization and representational limits of graph neural networks
V Garg, S Jegelka, T Jaakkola
International Conference on Machine Learning, 3419-3430, 2020
3062020
On learning to localize objects with minimal supervision
HO Song, R Girshick, S Jegelka, J Mairal, Z Harchaoui, T Darrell
International Conference on Machine Learning (ICML), 2014
2892014
Resnet with one-neuron hidden layers is a universal approximator
H Lin, S Jegelka
Advances in neural information processing systems 31, 6169-6178, 2018
2702018
What Can Neural Networks Reason About?
K Xu, J Li, M Zhang, SS Du, K Kawarabayashi, S Jegelka
arXiv preprint arXiv:1905.13211, 2019
2652019
Submodularity beyond submodular energies: coupling edges in graph cuts
S Jegelka, J Bilmes
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on …, 2011
2452011
Batched large-scale bayesian optimization in high-dimensional spaces
Z Wang, C Gehring, P Kohli, S Jegelka
International Conference on Artificial Intelligence and Statistics, 745-754, 2018
2072018
Weakly-supervised discovery of visual pattern configurations
HO Song, YJ Lee, S Jegelka, T Darrell
Advances in neural information processing systems 27, 1637-1645, 2014
1932014
Fast semidifferential-based submodular function optimization
R Iyer, S Jegelka, J Bilmes
International Conference on Machine Learning (ICML), 2013
1432013
Adversarially robust optimization with gaussian processes
I Bogunovic, J Scarlett, S Jegelka, V Cevher
Advances in neural information processing systems 31, 5760-5770, 2018
1412018
Distributionally robust optimization and generalization in kernel methods
M Staib, S Jegelka
Advances in Neural Information Processing Systems, 9134-9144, 2019
1402019
Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
E Kim, Z Jensen, A van Grootel, K Huang, M Staib, S Mysore, HS Chang, ...
Journal of Chemical Information and Modeling 60 (3), 1194-1201, 2020
139*2020
Virtual screening of inorganic materials synthesis parameters with deep learning
E Kim, K Huang, S Jegelka, E Olivetti
npj Computational Materials 3 (53), 2017
1372017
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