Questions tagged [representation]
The representation tag has no summary.
42 questions
1
vote
0
answers
34
views
Deep State Space Models for Latent Variable
I am working on a task where a one-dimensional dynamic latent variable will be estimated using a set of high-dimensional (both structured and unstructured) observables. It is important for me to have ...
- 13
2
votes
0
answers
38
views
Ultra-Minimalist Visualization for Term Frequency Table (Alternative for Tag Cloud)
Disclaimer: I have no background in Data Science or Statistics.
I used AI to extract a vast list of topical keywords, from thousands of news articles, published by dozens of Tech News Publications, ...
- 121
1
vote
2
answers
5k
views
Splitting documents with langchain when a sentence straddles the a page break
I've been following this guide to Langchain: https://learn.deeplearning.ai/langchain-chat-with-your-data/lesson/3/document-splitting
It seems like the Langchain document loaders treat each page of a ...
- 153
0
votes
1
answer
151
views
Deepstack autoencoder
I'm trying to go through the first edition tabular challenge on Kaggle. Obviously my first few trials results did not satisfy me, so I went to see how other people did, and in the post of the first ...
- 63
1
vote
1
answer
977
views
Is n-gram a special instance of bag of word? What are their differences?
Is n-gram a special instance of bag of word? What are their differences? From my understanding, n-gram is when replacing the words in bag of words with n-grams, and follow the same procedures to ...
- 441
1
vote
0
answers
301
views
Is normalization of word embeddings important?
I am doing actor-critic reinforcement learning for an environment that is best represented as a "bag-of-words". For this reason, I have opted to use a single body, multi-head approach for ...
1
vote
1
answer
44
views
Does feature engineering require absolute accuracy?
Sometimes when I'm studying the datasets, the text field is particularly challenging to handle. For whatever features I want to derive from the text fields, I try to apply some heuristic to ...
- 441
1
vote
0
answers
66
views
Why are wavelet transforms not scale-equivariant?
One can rely on continuous wavelets to build a multi-resolution analysis that is equivariant ("covariant") under the action of a discrete subgroup of translation.
When not downsampled,
the ...
- 111
0
votes
1
answer
45
views
Output representation for a neural network to learn grid-based game with multiple units
I have a round based game played on a grid map with multiple units that I would like to control in some fashion using neural network (NN). All of the units are moved at once. Each unit can move in any ...
- 101
1
vote
1
answer
2k
views
How can i get the vector of word using BERT?
I need to get word-vectors using BERT and got this function that i think it should be the one i need
...
- 125
0
votes
1
answer
67
views
How to represent a "switch"-like behavior in a neural network?
I have three input variables $x_1$, $x_2$ and $d$, where $x_1$ and $x_2$ are numerical variables and $d$ is a dummy variable that takes the value of 1 or 2. How to represent the part of a neural ...
- 101
0
votes
2
answers
6k
views
How to JUST represent words as embeddings by pretrained BERT?
I don't have enough data (i.e. I don't have enough texts) --- have only around 4k words in my dictionary. I need to compare given words, then I need to representate it as embedding.
After the ...
- 135
2
votes
2
answers
321
views
KNN efficient implementation
The KNN algorithm is very handy and particularly suited to some of my problems, but I can't find any resources on how to implement it in production.
As a comparative example, when I use a neural ...
- 21
5
votes
1
answer
4k
views
Difference between NCE-Loss and InfoNCE-Loss
I started looking into word2vec and was wondering what the connection/difference between the NCE-Loss and the infoNCE-Loss is. I get the basic idea of both.
I have a hard time deriving one from ...
- 51
6
votes
1
answer
11k
views
What are latent representations?
I am reading some research papers about graph convolutional neural networks and I have seen the term "latent representations" used a lot. For instance, "the model was able to learn ...
- 61