Kun Xu

Orcid: 0000-0002-0461-5876

Affiliations:
  • Tsinghua University, Tsinghua-Fuzhou Institute for Data Technology, Beijing, China


According to our database1, Kun Xu authored at least 19 papers between 2016 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2022
Triple Generative Adversarial Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Bi-level Score Matching for Learning Energy-based Latent Variable Models.
CoRR, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
CoRR, 2020

Boosting Adversarial Training with Hypersphere Embedding.
CoRR, 2020

Learning Implicit Generative Models by Teaching Density Estimators.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Understanding and Stabilizing GANs' Training Dynamics Using Control Theory.
Proceedings of the 37th International Conference on Machine Learning, 2020

Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness.
Proceedings of the 8th International Conference on Learning Representations, 2020

To Relieve Your Headache of Training an MRF, Take AdVIL.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Understanding and Stabilizing GANs' Training Dynamics with Control Theory.
CoRR, 2019

Multi-objects Generation with Amortized Structural Regularization.
CoRR, 2019

Adversarial Variational Inference and Learning in Markov Random Fields.
CoRR, 2019

Improving Adversarial Robustness via Promoting Ensemble Diversity.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Deep Structured Generative Models.
CoRR, 2018

Learning Implicit Generative Models by Teaching Explicit Ones.
CoRR, 2018

2017
Triple Generative Adversarial Nets.
CoRR, 2017

2016
Neuron Segmentation Based on CNN with Semi-Supervised Regularization.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016


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