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Found 8 papers, 1 papers with code
Structure-Preserving Transformers for Sequences of SPD Matrices
In recent years, Transformer-based auto-attention mechanisms have been successfully applied to the analysis of a variety of context-reliant data types, from texts to images and beyond, including data from non-Euclidean geometries.
Ranked #1 on
Sleep Stage Detection
on MASS SS3
(Macro-averaged Accuracy metric)
Maximal Independent Sets for Pooling in Graph Neural Networks
Convolutional Neural Networks (CNNs) have enabled major advances in image classification through convolution and pooling.
Maximal Independent Vertex Set applied to Graph Pooling
Consequently, our method does not discard any vertex information nor artificially increase the density of the graph.
A new Sinkhorn algorithm with Deletion and Insertion operations
Conversely, the remaining elements of V2 correspond to the image of the epsilon pseudo element of V1.
Improved local search for graph edit distance
Among different classes of heuristic algorithms that were proposed to compute approximate solutions, local search based algorithms provide the tightest upper bounds for GED.
Generalized Median Graph via Iterative Alternate Minimizations
Computing a graph prototype may constitute a core element for clustering or classification tasks.
Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks
In this paper, we propose a new hand gesture recognition method based on skeletal data by learning SPD matrices with neural networks.
A neural network based on SPD manifold learning for skeleton-based hand gesture recognition
A new type of layer is proposed for the third stage, based on a variant of stochastic gradient descent on Stiefel manifolds.
