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Junbo Zhao
Junbo Zhao
Other namesJake Zhao, Junbo Zhao (Jake)
Zhejiang University, ZJU100 Young Professor
Verified email at zju.edu.cn - Homepage
Title
Cited by
Cited by
Year
Character-level convolutional networks for text classification
X Zhang, J Zhao, Y LeCun
Advances in neural information processing systems 28, 2015
73842015
End to end learning for self-driving cars
A (All equal contribution), M Bojarski, D Del Testa, D Dworakowski, ...
NIPS 2016 Symposium, 2016
5569*2016
BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer
F Sun, J Liu, J Wu, C Pei, X Lin, W Ou, P Jiang
Proceedings of the 28th ACM international conference on information and …, 2019
22602019
Energy-based generative adversarial network
J Zhao, M Mathieu, Y LeCun
ICLR 2017, 2016
16392016
Deep graph library: Towards efficient and scalable deep learning on graphs
M Wang, L Yu, D Zheng, Q Gan, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ...
arXiv preprint arXiv:1909.01315, 2019
8342019
Disentangling factors of variation in deep representation using adversarial training
MF Mathieu, J Zhao, A Ramesh, P Sprechmann, Y LeCun
Advances in Neural Information Processing Systems, 5041-5049, 2016
5702016
Levenshtein transformer
J Gu, C Wang, J Zhao
Advances in neural information processing systems 32, 2019
4022019
Adversarially Regularized Autoencoders
J Zhao, Y Kim, K Zhang, AM Rush, Y LeCun
ICML 2018, 2017
3682017
Stacked What-Where Auto-encoders
YLC Junbo Zhao, Michael Mathieu, Ross Goroshin
ICLR 2016, 2016
364*2016
Pico: Contrastive label disambiguation for partial label learning
H Wang, R Xiao, Y Li, L Feng, G Niu, G Chen, J Zhao
International conference on learning representations, 2022
1532022
Identification of potent antimicrobial peptides via a machine-learning pipeline that mines the entire space of peptide sequences
J Huang, Y Xu, Y Xue, Y Huang, X Li, X Chen, Y Xu, D Zhang, P Zhang, ...
Nature Biomedical Engineering 7 (6), 797-810, 2023
952023
Adversarially regularized autoencoders for generating discrete structures
Y Kim, K Zhang, AM Rush, Y LeCun
arXiv preprint arXiv:1706.04223 4, 2.2-6.2, 2017
732017
A critical look at the current train/test split in machine learning
J Tan, J Yang, S Wu, G Chen, J Zhao
arXiv preprint arXiv:2106.04525, 2021
692021
Prompt as triggers for backdoor attack: Examining the vulnerability in language models
S Zhao, J Wen, LA Tuan, J Zhao, J Fu
arXiv preprint arXiv:2305.01219, 2023
682023
Glomo: Unsupervised learning of transferable relational graphs
Z Yang, J Zhao, B Dhingra, K He, WW Cohen, RR Salakhutdinov, ...
Advances in Neural Information Processing Systems 31, 2018
66*2018
Pianotree vae: Structured representation learning for polyphonic music
Z Wang, Y Zhang, Y Zhang, J Jiang, R Yang, J Zhao, G Xia
arXiv preprint arXiv:2008.07118, 2020
642020
Promix: Combating label noise via maximizing clean sample utility
R Xiao, Y Dong, H Wang, L Feng, R Wu, G Chen, J Zhao
arXiv preprint arXiv:2207.10276, 2022
522022
Maybe only 0.5% data is needed: A preliminary exploration of low training data instruction tuning
H Chen, Y Zhang, Q Zhang, H Yang, X Hu, X Ma, Y Yanggong, J Zhao
arXiv preprint arXiv:2305.09246, 2023
412023
Solar: Sinkhorn label refinery for imbalanced partial-label learning
H Wang, M Xia, Y Li, Y Mao, L Feng, G Chen, J Zhao
Advances in neural information processing systems 35, 8104-8117, 2022
352022
Deep graph library: towards efficient and scalable deep learning on graphs. CoRR abs/1909.01315 (2019)
M Wang, L Yu, QG Da Zheng, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ...
arXiv preprint arXiv:1909.01315, 2019
342019
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