Publications (144)
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
Khang Nguyen, Hieu Nong, Vinh Nguyen +3
Graph Neural Networks (GNNs) had been demonstrated to be inherently susceptible to the problems of over-smoothing and over-squashing. These issues prohibit the ability of GNNs to m…
Revisit Visual Prompt Tuning: The Expressiveness of Prompt Experts
Minh Le, Anh Nguyen, Huy Nguyen +3
Visual Prompt Tuning (VPT) has proven effective for parameter-efficient adaptation of pre-trained vision models to downstream tasks by inserting task-specific learnable prompt toke…
On Label Shift in Domain Adaptation via Wasserstein Distance
Trung Le, Dat Do, Tuan Nguyen +4
We study the label shift problem between the source and target domains in general domain adaptation (DA) settings. We consider transformations transporting the target to source dom…
Flow-based Alignment Approaches for Probability Measures in Different Spaces
Tam Le, Nhat Ho, Makoto Yamada
Gromov-Wasserstein (GW) is a powerful tool to compare probability measures whose supports are in different metric spaces. GW suffers however from a computational drawback since it…
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen +1
Mixture-of-experts (MoE) model incorporates the power of multiple submodels via gating functions to achieve greater performance in numerous regression and classification applicatio…
Designing Robust Transformers using Robust Kernel Density Estimation
Xing Han, Tongzheng Ren, Tan Minh Nguyen +3
Recent advances in Transformer architectures have empowered their empirical success in a variety of tasks across different domains. However, existing works mainly focus on predicti…