Questions tagged [embeddings]
For questions about embeddings (not necessarily just word embeddings, for which there is a specific tag) in the context of machine learning.
10
questions
0
votes
1answer
25 views
Are the Word2Vec encoding available online [closed]
I am trying to do an NLP project and was wondering if there is anywhere online where the Word2Vec encoding are stored.
I want to search up a word and see what its encoding is. I have tried looking but ...
0
votes
1answer
29 views
Converting age and sex variables to a 64-unit dense layer
I am studying a preprint for my own learning (https://www.medrxiv.org/content/medrxiv/early/2020/04/27/2020.04.23.20067967.full.pdf) and I am befuddled by the following detail of the neural network ...
0
votes
0answers
34 views
Seq2Seq Modelling: when implementing some machine translation net, how are special tokens embedded?
When implementing any encoder-decoder network for machine translation, during training we provide the true output sentence to the decoder so that the context vector (from source language) may be ...
0
votes
0answers
22 views
How to change the number of input neurons in embedding layer?
I was building a recommender system using Tensorflow recommenders (TFRS) library . I was following the official tutorial for ranking model , where they have used two-tower model. The part where I have ...
0
votes
0answers
19 views
Sparse Multi-hot encoding and autoencoders
I'm working with graph neural networks.
I have a large graph. Each node has 4 features [A,B,C,D]:
2 categorical with high cardinality: 86k (A) and 148k (B) different features
2 integer with ranges: [...
1
vote
0answers
20 views
How does the embeddings work in vision transformer from paper?
I get the part from the paper where the image is split into P say 16x16 (smaller images) patches and then you have to ...
1
vote
0answers
21 views
Is there any research work that shows that we should explicitly mark the word boundaries for 1D CNNs?
I'm doing character embedding for NLP tasks using one-dimensional convolutional neural networks (see Chiu and Nichols (2016) for the motivation). I haven't found any empirical evidence of whether or ...
2
votes
1answer
64 views
In the machine learning literature, what does it mean to say that something is “embedded” in some space?
In the machine learning literature, I often see it said that something is "embedded" in some space. For instance, that something is "embedded" in feature space, or that our data ...
1
vote
1answer
49 views
What is the role of embeddings in a deep recurrent Q network?
When describing the model architecture for a deep recurrent q network, the authors of the paper Learning to Communicate with Deep Multi-Agent Reinforcement Learning
each agent consists of a recurrent ...
18
votes
4answers
5k views
What is the difference between latent and embedding spaces?
In general, the word "latent" means "hidden" and "to embed" means "to incorporate". In machine learning, the expressions "hidden (or latent) space" ...
