为此,我们提出了一种基于核感知图提示学习(Kernel-Aware Graph Prompt Learning)的框架,简称 KAG-prompt,用于在 FSAD 任务中推理视觉特征的跨层关系。具体而言,我们构建了一个核感知层次图(Kernel-aware Hierarchical Graph),其中不同层次的特征(关注不同尺度的异常区域)被视为图的节点,而任意两个节点之间的关系则构...
To address these limitations, we propose a Subgraph-aware Graph Kernel Neural Network (SubKNet) for link prediction in biological networks. Specifically, SubKNet extracts a subgraph for each node pair and feeds it into a graph kernel neural network, which decomposes each subgraph into a ...
.github Removed --build-config Apr 2, 2025 assets README changes Mar 26, 2025 auxiliary fixed updater.py, fixed add_technique, and added extra credits Apr 8, 2025 docs removed VM::IDT_GDT_SCAN Apr 11, 2025 papers better docs update, updated readme graph, etc ...
It turns out that, when strict memory budget constraints have to be enforced, working in feature space, given the current state-of-the-art on graph kernels, is more than a viable alternative to dual approaches, both in terms of speed and classification performance...
- [ ] update the Hyper-X graph with the cpu manufacturer part - [ ] add a .so, .dll, and .dylib shared object files in the release - [X] make a struct version as an alternative - [ ] add the license style like in ffmpeg https://github.com/FFmpeg/FFmpeg/tree/master?tab=Licen...
To address these limitations, we propose a Subgraph-aware Graph Kernel Neural Network (SubKNet) for link prediction in biological networks. Specifically, SubKNet extracts a subgraph for each node pair and feeds it into a graph kernel neural network, which decomposes each subgraph into a ...
Graph Convolutional Networks (GCNs) are widely applied in classification tasks by aggregating the neighborhood information of each sample to output robust ... Y Zhu,J Ma,C Yuan,... - 《Information Fusion》 被引量: 0发表: 2021年 Multi-domain modeling of atrial fibrillation detection with twin ...
The top-ranked graphlets are either visually or semantically salient according to human perception. They are linked into a path to simulate human gaze shifting. Finally, we calculate the gaze shifting kernel (GSK) based on the discovered paths from a set of images. Experiments on the USC ...
We present a software approach to address the data latency issue for certain GPU applications. Each application is modeled as a kernel graph, where the nodes represent individual GPU kernels and the edges capture data dependencies. Our technique exploits the GPU L2 cache to accelerate parameter ...
First, a weakly supervised embedding algorithm projects the local image descriptors (i.e., graphlets) into a pre-specified semantic space. Afterward, each graphlet can be represented by multiple visual features at both low-level and high-level. As humans typically attend to a small fraction of...