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```ruby
require 'matrix'
class RecommendationSystem
def initialize(user_preferences, space_profiles)
@user_preferences = user_preferences
@space_profiles = space_profiles
end
…
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really not clear from paper: 'computed as cosine similarity
with annealing between the encodings hx and
hy. It starts at 1 and ends atp
d, linearly increasing
over the first 10K training batches.'…
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Hi,
Very nice work!
How to generate visual image of 'Similarity of Attention Outputs' as shown in Figure 4?
Could the author share the code for visualization??
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I wonder how the relatedness test would work for cosine similarity.
given crossnobis RDMs for multiple subjects and a model, cosine similarities cannot be tested against zero.
is there a simple way …
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I saw that currently the cosine similarity is computed on a vector by vector basis, which can become quite slow for a big amount of samples.
I recently had the same issue on a personal project with a…
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When calculating the cosine similarity between the embeddings (mean pooling as implemented using sentence-transformers) of random english words is giving scores well above 0.9 for some reason I can't …
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In explore_context2vec.py, when got context_v and target_v, why use w again?
You use the w to get the context_v, didn't you?
```
def mult_sim(w, target_v, context_v):
target_similarity = w.dot…
mfxss updated
6 years ago
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I attempted to apply the method to clustering tweets. I may be misunderstanding how this works, but running it with cosine_similarity(matrix name) only worked when my data was very small (500 tweets)…
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cypher_queries/method1_queries.cql
change:
line 35: et al
gds.alpha.similarity.cosine
to:
gds.similarity.cosine
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Hello Team,
Thank you for your amazing work on this model. I was able to reproduce your remarkable results. I am looking to contribute and develop downstream inference using faiss but I am running …