to identify surface water and near-water sediment pixels in multispectral images. The CGAP enhances the graph-based active learning pipeline (Chen et al., 2023), which outperforms methods such as ...

Our software, called gala (graph-based active learning of agglomeration ... and Chklovskii, D. B. (2013). Machine learning of hierarchical clustering to segment 2D and 3D images. PLoS ONE 8:e71715.

This python package is devoted to efficient implementations of modern graph-based learning algorithms for semi-supervised learning, active learning ... of the 37th International Conference on Machine ...

Most ML algorithms require annotated text, images, speech, audio or video data. But, with the right resources and right amount of data, practitioners can leverage active learning. Active learning is ...

The accelerating power of machine ... images whose appearance can be controlled with free-form medical text prompts. A digital pathology–artificial intelligence framework that leverages active ...

Their proposed architecture, for example, takes images and free-form texts as node features." The takeaway? It may be early days for graph-based machine learning reasoning, but initial results ...

Also: Google Next 2018: A deeper dive on AI and machine learning advances The paper explicitly draws upon work for more than a decade now on "graph neural networks." It also echoes some of the ...

PyKale - A PyTorch library that provides a unified pipeline-based API for knowledge-aware machine learning on graphs, images, texts, and videos to accelerate interdisciplinary research. Our group ...