Hung Bui
26 papers · 2008–2022 · 9 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (16) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (6) π£ Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(16)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Grand Slam
π€
Dynamic Duo
(10)
π
Triple Crown
π
Keyword Champion
(2)
π
Trend Setter
β‘
Prolific Year
(9)
π
Conference Pioneer
ποΈ
Keyword Collector
(51)
π
Century Club
(26)
π₯
Unstoppable
(7)
Conferences
ICML (7)
IJCAI (5)
ICLR (4)
NIPS (4)
AISTATS (2)
AAAI (1)
CVPR (1)
JMLR (1)
NAACL (1)
Top co-authors
Keywords
optimal transport
(4)
wasserstein distance
(3)
latent space
(3)
variational inference
(3)
domain adaptation
(3)
generative adversarial network
(3)
variational autoencoder
(2)
transfer learning
(2)
representation learning
(2)
sinkhorn algorithm
(2)
entropic regularization
(2)
hidden markov model
(2)
gibbs sampling
(2)
computational complexity
(2)
optimal control
(2)
model-based reinforcement learning
(2)
dynamical system
(2)
bayesian nonparametrics
(2)
probability measure
(2)
reparameterization trick
(2)
Papers
On Transportation of Mini-batches: A Hierarchical Approach
ICML 2022
Temporal Predictive Coding For Model-Based Planning In Latent Space
ICML 2021
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
NIPS 2021
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior
AAAI 2021
Structured Dropout Variational Inference for Bayesian Neural Networks
NIPS 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation
NIPS 2021
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
ICLR 2021
Distributional Sliced-Wasserstein and Applications to Generative Modeling
ICLR 2021
On efficient multilevel Clustering via Wasserstein distances
JMLR 2021
LAMDA: Label Matching Deep Domain Adaptation
ICML 2021
Vec2Face: Unveil Human Faces From Their Blackbox Features in Face Recognition
CVPR 2020
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems
ICML 2020
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control
ICLR 2020
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm
ICML 2020
Predictive Coding for Locally-Linear Control
ICML 2020
Training Variational Autoencoders with Buffered Stochastic Variational Inference
AISTATS 2019
Learning Generative Adversarial Networks from Multiple Data Sources
IJCAI 2019
Three-Player Wasserstein GAN via Amortised Duality
IJCAI 2019
The Context-Dependent Additive Recurrent Neural Net
NAACL 2018
Robust Locally-Linear Controllable Embedding
AISTATS 2018
A DIRT-T Approach to Unsupervised Domain Adaptation
ICLR 2018
Discriminative Bayesian Nonparametric Clustering
IJCAI 2017
Large-scale Online Kernel Learning with Random Feature Reparameterization
IJCAI 2017
Practical Linear Models for Large-Scale One-Class Collaborative Filtering
IJCAI 2016
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts
ICML 2014
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
NIPS 2008