Khai Nguyen
29 papers · 2021–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (7) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π Cross-Pollinator (9)
π§
Keyword Pioneer
π
Renaissance Researcher
(8)
π€
Dynamic Duo
(27)
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Triple Crown
π₯
Unstoppable
(5)
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Century Club
(29)
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Keyword Collector
(96)
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Prolific Year
(7)
Conferences
NIPS (10)
ICLR (8)
ICML (5)
AISTATS (3)
CORL (1)
CVPR (1)
EMNLP (1)
Top co-authors
Research topics
Keywords
optimal transport
(7)
sliced wasserstein distance
(6)
maximum likelihood estimation
(3)
parameter estimation
(3)
gradient flow
(3)
entropic regularization
(2)
transformer architecture
(2)
deep generative model
(2)
multi-head attention
(2)
sliced wasserstein
(2)
domain adaptation
(2)
probability measure
(2)
mixture of expert
(2)
mini batch
(2)
machine translation
(1)
attention mechanism
(1)
self-attention mechanism
(1)
shape correspondence
(1)
image generation
(1)
point cloud
(1)
Papers
DEQ-MPC : Deep Equilibrium Model Predictive Control
CORL 2025
Lightspeed Geometric Dataset Distance via Sliced Optimal Transport
ICML 2025
Towards Marginal Fairness Sliced Wasserstein Barycenter
ICLR 2025
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning
CVPR 2024
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions
NIPS 2024
On Parameter Estimation in Deviated Gaussian Mixture of Experts
AISTATS 2024
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts
AISTATS 2024
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
ICLR 2024
Quasi-Monte Carlo for 3D Sliced Wasserstein
ICLR 2024
Sliced Wasserstein Estimation with Control Variates
ICLR 2024
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation
ICLR 2024
Sliced Wasserstein with Random-Path Projecting Directions
ICML 2024
Hierarchical Sliced Wasserstein Distance
ICLR 2023
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction
ICML 2023
Designing Robust Transformers using Robust Kernel Density Estimation
NIPS 2023
Markovian Sliced Wasserstein Distances: Beyond Independent Projections
NIPS 2023
Energy-Based Sliced Wasserstein Distance
NIPS 2023
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models
NIPS 2023
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity
AISTATS 2022
Improving Transformer with an Admixture of Attention Heads
NIPS 2022
On Transportation of Mini-batches: A Hierarchical Approach
ICML 2022
Improving Mini-batch Optimal Transport via Partial Transportation
ICML 2022
Amortized Projection Optimization for Sliced Wasserstein Generative Models
NIPS 2022
FourierFormer: Transformer Meets Generalized Fourier Integral Theorem
NIPS 2022
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution
NIPS 2022
Neural Re-rankers for Evidence Retrieval in the FEVEROUS Task
EMNLP 2021
Structured Dropout Variational Inference for Bayesian Neural Networks
NIPS 2021
Distributional Sliced-Wasserstein and Applications to Generative Modeling
ICLR 2021
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
ICLR 2021