Questions tagged [non-euclidean-data]

For questions related to non-Euclidean data, such as graphs or manifolds. Geometric deep learning is an application of deep learning to non-Euclidean data.

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Distance functions used in clustering analysis

From what I've seen in clustering, distance is taken as a hyper parameter (which is to be selected) when inferring the relationships/clusters between points. Examples of distances I've come across ...
ABIM's user avatar
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Linear Discriminant Analysis on a transformed space

Let $S$ be a finite subset of a $\mathbb{R}^k$ partitioned into $N$ subsets $S_1, \ldots, S_N$ and let $n_j = |S_j|$. The between-groups sum of squares of the partition is defined as $$bSS(S_1,\ldots, ...
Alberto's user avatar
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What exactly is a grid-like topology according to the book Deep Learning?

I am reading this book called "Deep Learning" (by Goodfellow, Bengio and Courville). On page 326, in the first paragraph, it says: CNNs, are a specialized kind of neural network for ...
Aether's user avatar
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What is non-Euclidean data?

What is non-Euclidean data? Here are some sub-questions Where does this type of data arise? I have come across this term in the context of geometric deep learning and graph neural networks. ...
nbro's user avatar
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