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I noticed that the library computes the similarity between vectors in a strange manner. The scores are not really cosine similarity but cross-products. @jwijffels , do you think it is intentional?
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**Context:** Currently we have only implemented Euclidean Distance (L2 norm) (can read more about it from `l2.rs` file in `Utils` module)
As a starting point to get familiar with the codebase, we w…
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### Is your feature request related to a problem?
Feature request #2385 discusses fuzzy string matching that was implemented in PR #1904.
@tobiemh mentioned three not-yet-implemented string distance…
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### 🚀 The feature, motivation and pitch
I recently came across the paper [A Survey on Oversmoothing in Graph Neural Networks](https://arxiv.org/abs/2303.10993) and thougt that having a ready-to-use…
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https://github.com/meiersi0/cma-week3/blob/dfcde1718d6943b5c21bdc764785c6550fa9d13f/week3.R#L174-L178the idea was to also compare different similarity measures..
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We would like to be able to store relevant similarity measures between signatures, but are not sure what measures we will want in the future. These will be updated regularly in the future as new signa…
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In JgraphT library, is there any algorithm that I can compute the graph similarity for example structural equivalence that can be calculated by Cosine similarity?
This Wikipedia page has the inform…
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Fatima, you had this paper on alternative similarity measures to the usual euclidean distance, perhaps you could try to implement this.
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### Feature request
Add an option to the RLOOTrainer that enables the use of string-based reward models, such as BLEU and Levenshtein distance, for evaluating model outputs.
### Motivation
Curren…
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Title is fairly self explanatory, I've found the need for cosine distance at various times (and other distance metrics) that probably fit well in ndarray-stats. Maybe here we can decided on a few diff…