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Title
Cited by
Cited by
Year
Stein variational gradient descent: A general purpose bayesian inference algorithm
Q Liu, D Wang
Advances in neural information processing systems (NeurIPS), 2378-2386, 2016
11072016
Learning to draw samples: With application to amortized mle for generative adversarial learning
D Wang, Q Liu
arXiv preprint arXiv:1611.01722, 2016
2012016
Multi-scale high-resolution vision transformer for semantic segmentation
J Gu, H Kwon, D Wang, W Ye, M Li, YH Chen, L Lai, V Chandra, DZ Pan
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
1862022
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
C Gong, D Wang, M Li, V Chandra, Q Liu
Conference on Computer Vision and Pattern Recognition (CVPR) 2021, 2020
1262020
An Optimization View on Dynamic Routing Between Capsules
D Wang, Q Liu
Workshop track - ICLR 2018, 2018
1202018
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
D Wang, M Li, C Gong, V Chandra
Conference on Computer Vision and Pattern Recognition (CVPR) 2021, 2020
1102020
Improving neural language modeling via adversarial training
D Wang, C Gong, Q Liu
Proceedings of the 36th International Conference on Machine Learning (ICML), 2019
1102019
Entity disambiguation by knowledge and text jointly embedding
W Fang, J Zhang, D Wang, Z Chen, M Li
Proceedings of the 20th SIGNLL conference on computational natural language …, 2016
1092016
Vision Transformers with Patch Diversification
C Gong, D Wang, M Li, V Chandra, Q Liu
arXiv preprint arXiv:2104.12753, 2021
83*2021
Learning to draw samples with amortized stein variational gradient descent
Y Feng, D Wang, Q Liu
Conference on Uncertainty in Artificial Intelligence (UAI), 2017
792017
Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning
C Gong, Z Jiang, D Wang, Y Lin, Q Liu, DZ Pan
International Conference On Computer Aided Design (ICCAD), 1-7, 2019
732019
Nasvit: Neural architecture search for efficient vision transformers with gradient conflict-aware supernet training
C Gong, D Wang
ICLR Proceedings 2022, 2022
70*2022
Stein variational gradient descent with matrix-valued kernels
D Wang, Z Tang, C Bajaj, Q Liu
Advances in neural information processing systems (NeurIPS), 7836-7846, 2019
692019
AlphaNet: Improved Training of Supernets with Alpha-Divergence
D Wang, C Gong, M Li, Q Liu, V Chandra
International Conference on Machine Learning (ICML) 2021, 2021
682021
Variational inference with tail-adaptive f-divergence
D Wang, H Liu, Q Liu
Advances in Neural Information Processing Systems (NeurIPS), 5737-5747, 2018
612018
Stein Variational Message Passing for Continuous Graphical Models
D Wang, Z Zeng, Q Liu
International Conference on Machine Learning (ICML), 2017
572017
AlphaMatch: Improving Consistency for Semi-supervised Learning with Alpha-divergence
C Gong, D Wang, Q Liu
Conference on Computer Vision and Pattern Recognition (CVPR) 2021, 2020
482020
Splitting steepest descent for growing neural architectures
Q Liu, L Wu, D Wang
Advances in Neural Information Processing Systems (NeurIPS), 10656-10666, 2019
462019
Stein variational gradient descent as moment matching
Q Liu, D Wang
Advances in Neural Information Processing Systems (NeurIPS), 8854-8863, 2018
452018
Nonlinear stein variational gradient descent for learning diversified mixture models
D Wang, Q Liu
International Conference on Machine Learning (ICML), 6576-6585, 2019
252019
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