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Found 2 papers, 0 papers with code
GraphMDN: Leveraging graph structure and deep learning to solve inverse problems
The recent introduction of Graph Neural Networks (GNNs) and their growing popularity in the past few years has enabled the application of deep learning algorithms to non-Euclidean, graph-structured data.
Graph Classification
Multi-Hypotheses 3D Human Pose Estimation
+2
Landslide Geohazard Assessment With Convolutional Neural Networks Using Sentinel-2 Imagery Data
In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide risk mitigation.
