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Found 6 papers, 6 papers with code
Frequency Attention for Knowledge Distillation
Inspired by the benefits of the frequency domain, we propose a novel module that functions as an attention mechanism in the frequency domain.
Optimal Transport Model Distributional Robustness
Interestingly, our developed theories allow us to flexibly incorporate the concept of sharpness awareness into training, whether it's a single model, ensemble models, or Bayesian Neural Networks, by considering specific forms of the center model distribution.
Vision Transformer Visualization: What Neurons Tell and How Neurons Behave?
Our approach departs from the computational process of ViTs with a focus on visualizing the local and global information in input images and the latent feature embeddings at multiple levels.
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection
Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks.
STEM: An Approach to Multi-Source Domain Adaptation With Guarantees
To address the second challenge, we propose to bridge the gap between the target domain and the mixture of source domains in the latent space via a generator or feature extractor.
STEM: An Approach to Multi-Source Domain Adaptation With Guarantees
To address the second challenge, we propose to bridge the gap between the target domain and the mixture of source domains in the latent space via a generator or feature extractor.
Multi-Source Unsupervised Domain Adaptation
Unsupervised Domain Adaptation
