Ruiyi Zhang
Ruiyi Zhang
Verified email at cs.duke.edu - Homepage
Title
Cited by
Cited by
Year
Improving Adversarial Text Generation by Modeling the Distant Future
R Zhang, C Chen, Z Gan, W Wang, D Shen, G Wang, Z Wen, L Carin
Association for Computational Linguistics, 2019
59*2019
Topic-Guided Variational Autoencoders for Text Generation
W Wang, Z Gan, H Xu, R Zhang, G Wang, D Shen, C Chen, L Carin
Annual Conference of the North American Chapter of the Association for …, 2019
462019
Cyclical stochastic gradient MCMC for Bayesian deep learning
R Zhang, C Li, J Zhang, C Chen, AG Wilson
arXiv preprint arXiv:1902.03932, 2019
322019
Policy Optimization as Wasserstein Gradient Flows
R Zhang, C Chen, C Li, L Carin
International Conference on Machine Learning, 2018
322018
A Unified Particle-optimization Framework for Scalable Bayesian Sampling
C Chen, R Zhang, W Wang, B Li, L Chen
Uncertainty in Artificial Intelligence, 2018
292018
Improving Sequence-to-Sequence Learning via Optimal Transport
L Chen, Y Zhang, R Zhang, C Tao, Z Gan, H Zhang, B Li, D Shen, C Chen, ...
International Conference on Learning Representation, 2019
282019
GenDICE: Generalized Offline Estimation of Stationary Values
R Zhang, B Dai, L Li, D Schuurmans
International Conference on Learning Representation, 2020
212020
Variational inference and model selection with generalized evidence bounds
C Tao, L Chen, R Zhang, R Henao, LC Duke
International conference on machine learning, 893-902, 2018
192018
Learning Structural Weight Uncertainty for Sequential Decision-Making
R Zhang, C Li, C Chen, L Carin
International Conference on Artificial Intelligence and Statistics, 1137--1146, 2018
182018
Text-based interactive recommendation via constraint-augmented reinforcement learning
R Zhang, T Yu, Y Shen, H Jin, C Chen
Advances in Neural Information Processing Systems, 15214-15224, 2019
15*2019
Stochastic particle-optimization sampling and the non-asymptotic convergence theory
J Zhang, R Zhang, C Chen, L Carin
International Conference on Artificial Intelligence and Statistics, 2020
142020
Understanding and Accelerating Particle-Based Variational Inference
C Liu, J Zhuo, P Cheng, R Zhang, J Zhu, L Carin
International Conference on Machine Learning, 4082-4092, 2019
142019
Scalable Thompson Sampling via Optimal Transport
R Zhang, Z Wen, C Chen, L Carin
International Conference on Artificial Intelligence and Statistics, 1137--1146, 2019
12*2019
Accelerated first-order methods on the wasserstein space for bayesian inference
C Liu, J Zhuo, P Cheng, R Zhang, J Zhu, L Carin
International Conference on Machine Learning, 2019
102019
Figure Captioning with Reasoning and Sequence-Level Training
C Chen, R Zhang, E Koh, S Kim, S Cohen, R Rossi
The IEEE Winter Conference on Applications of Computer Vision, 1537-1545, 2020
72020
Improving Textual Network Learning with Variational Homophilic Embeddings
W Wang, C Tao, Z Gan, G Wang, L Chen, X Zhang, R Zhang, Q Yang, ...
Advances in Neural Information Processing Systems, 2019
72019
Variational Annealing of GANs: A Langevin Perspective
C Tao, S Dai, L Chen, K Bai, J Chen, C Liu, R Zhang, G Bobashev, ...
International Conference on Machine Learning, 2019
62019
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
Z Wang, P Yu, Y Zhao, R Zhang, Y Zhou, J Yuan, C Chen
AAAI, 2020
32020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
B An, J Lyu, Z Wang, C Li, C Hu, F Tan, R Zhang, Y Hu, C Chen
Conference on Empirical Methods in Natural Language Processing, 2020
2*2020
Nested-Wasserstein Self-Imitation Learning for Sequence Generation
R Zhang, C Chen, Z Gan, Z Wen, W Wang, L Carin
International Conference on Artificial Intelligence and Statistics, 2020
22020
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Articles 1–20