Viet Huynh

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 22

Top Topics

Dirichlet Process

Variance Reduction

Nonparametric Bayesian

Top Venues

Publications

Viet Huynh, Buser Say, Peter Vogel, Lucy Cao, Geoffrey I. Webb, Aldeida Aleti
Rapid Identification of Protein Formulations with Bayesian Optimisation. ICMLA (2023)
Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. 22 (2021)
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
Neural Topic Model via Optimal Transport. ICLR (2021)
Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
Improved and Efficient Text Adversarial Attacks using Target Information. CoRR (2021)
He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI (2021)
Viet Huynh, Dinh Q. Phung, He Zhao
Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI (2021)
Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung
Text Generation with Deep Variational GAN. CoRR (2021)
He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
Topic Modelling Meets Deep Neural Networks: A Survey. CoRR (2021)
Nhan Dam, Trung Le, Viet Huynh, Dinh Phung
Stein Variational Gradient Descent with Variance Reduction. IJCNN (2020)
Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation. CoRR (2020)
Viet Huynh, He Zhao, Dinh Phung
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling. NeurIPS (2020)
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
Neural Sinkhorn Topic Model. CoRR (2020)
Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation. IJCNN (2020)
Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan
Probabilistic Multilevel Clustering via Composite Transportation Distance. AISTATS (2019)
Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
On Efficient Multilevel Clustering via Wasserstein Distances. CoRR (2019)
Tam Le, Viet Huynh, Nhat Ho, Dinh Q. Phung, Makoto Yamada
On Scalable Variant of Wasserstein Barycenter. CoRR (2019)
Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan
Probabilistic Multilevel Clustering via Composite Transportation Distance. CoRR (2018)
Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung
Multilevel Clustering via Wasserstein Means. ICML (2017)
Viet Huynh, Dinh Q. Phung
Streaming clustering with Bayesian nonparametric models. Neurocomputing 258 (2017)
Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le
Supervised Restricted Boltzmann Machines. UAI (2017)
Nhan Dam, Dinh Q. Phung, Ba-Ngu Vo, Viet Huynh
Forward-Backward Smoothing for Hidden Markov Models of Point Pattern Data. DSAA (2017)
Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui
Scalable Nonparametric Bayesian Multilevel Clustering. UAI (2016)
Viet Huynh, Dinh Q. Phung, Svetha Venkatesh
Streaming Variational Inference for Dirichlet Process Mixtures. ACML (2015)
Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) (2015)