Tan Minh Nguyen
23 papers · 2022–2025 · 4 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (29) 🏆 Keyword Champion (3)
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Century Club · Bronze
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Prolific Year · Prolific
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(3)
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(3)
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(2)
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optimal transport
(4)
graph neural network
(3)
gradient flow
(3)
radon transform
(3)
transformer architecture
(3)
sliced wasserstein distance
(2)
neural collapse
(2)
wasserstein distance
(2)
state space model
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generative model
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label propagation
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transformer
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model merging
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convergence analysis
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robustness
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language modeling
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sparse approximation
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attention mechanism
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feature learning
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support vector regression
(1)
Papers
CAMEx: Curvature-aware Merging of Experts
ICLR 2025
Demystifying the Token Dynamics of Deep Selective State Space Models
ICLR 2025
Distance-Based Tree-Sliced Wasserstein Distance
ICLR 2025
Equivariant Neural Functional Networks for Transformers
ICLR 2025
Equivariant Polynomial Functional Networks
ICML 2025
MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
ICLR 2025
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
ICML 2025
Spherical Tree-Sliced Wasserstein Distance
ICLR 2025
Tight Clusters Make Specialized Experts
ICLR 2025
Transformer Meets Twicing: Harnessing Unattended Residual Information
ICLR 2025
Tree-Sliced Wasserstein Distance: A Geometric Perspective
ICML 2025
Tree-Sliced Wasserstein Distance with Nonlinear Projection
ICML 2025
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
ICLR 2024
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach
AISTATS 2024
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model
ICML 2024
PIDformer: Transformer Meets Control Theory
ICML 2024
Revisiting Kernel Attention with Correlated Gaussian Process Representation
UAI 2024
A Primal-Dual Framework for Transformers and Neural Networks
ICLR 2023
Hierarchical Sliced Wasserstein Distance
ICLR 2023
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data
ICML 2023
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
ICML 2023
GRAND++: Graph Neural Diffusion with A Source Term
ICLR 2022
Improving Transformers with Probabilistic Attention Keys
ICML 2022