Tan Minh Nguyen
23 papers · 2022–2025 · 4 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+1 more ↓ Show less ↑
π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (4) π Cross-Pollinator (12) β‘ Prolific Year (12)
π
Century Club
(23)
Conferences
ICLR (12)
ICML (9)
AISTATS (1)
UAI (1)
Top co-authors
Keywords
graph neural network
(2)
feature learning
(1)
language modeling
(1)
message passing
(1)
neural collapse
(1)
coupled oscillator
(1)
imbalanced datum
(1)
linear attention
(1)
deep linear network
(1)
multi-head attention
(1)
kuramoto model
(1)
graph rewiring
(1)
ollivier-ricci curvature
(1)
simplex etf
(1)
long sequence
(1)
ricci curvature
(1)
class mean
(1)
node feature learning
(1)
transformer architecture
(1)
mixture of gaussian key
(1)
Papers
Tight Clusters Make Specialized Experts
ICLR 2025
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
ICML 2025
Tree-Sliced Wasserstein Distance with Nonlinear Projection
ICML 2025
Tree-Sliced Wasserstein Distance: A Geometric Perspective
ICML 2025
Equivariant Polynomial Functional Networks
ICML 2025
MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
ICLR 2025
Spherical Tree-Sliced Wasserstein Distance
ICLR 2025
Distance-Based Tree-Sliced Wasserstein Distance
ICLR 2025
CAMEx: Curvature-aware Merging of Experts
ICLR 2025
Equivariant Neural Functional Networks for Transformers
ICLR 2025
Demystifying the Token Dynamics of Deep Selective State Space Models
ICLR 2025
Transformer Meets Twicing: Harnessing Unattended Residual Information
ICLR 2025
Revisiting Kernel Attention with Correlated Gaussian Process Representation
UAI 2024
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
ICLR 2024
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model
ICML 2024
PIDformer: Transformer Meets Control Theory
ICML 2024
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach
AISTATS 2024
A Primal-Dual Framework for Transformers and Neural Networks
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
Hierarchical Sliced Wasserstein Distance
ICLR 2023
GRAND++: Graph Neural Diffusion with A Source Term
ICLR 2022
Improving Transformers with Probabilistic Attention Keys
ICML 2022