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16 views

Geometric structure of the output of a random weight neural network fed with random data

Take a model with random weigths: ...
Random Network's user avatar
1 vote
0 answers
27 views

References Request -- Research in Computer Vision

Apologies if this is not the correct forum for this request, but I figured I'd give it a shot. I'm looking for research in computer vision on shape recognition -- any shape. Most of the computer ...
luddite's user avatar
  • 11
0 votes
1 answer
51 views

graph convolution network

I am trying to understand papers and lectures on graph convolution networks but whenever I open some paper, I get lost on the very first page. I started with some videos like this and this and papers ...
Sarvagya Gupta's user avatar
1 vote
0 answers
530 views

ML techniques to classify simple polygons

I'm curious about suitability of Machine Learning techniques to classify grayscale images of polygons into categories defined by number of their sides, which will be kept small. Images will be "...
Paul Jurczak's user avatar
6 votes
0 answers
2k views

Why word embeddings learned from word2vec are linearly correlated

I was playing with CBOW from the word2vec program downloaded from https://code.google.com/archive/p/word2vec/ with some sequence data (peptides in this case). I was trying to get embeddings for amino ...
zyxue's user avatar
  • 1,176
2 votes
0 answers
932 views

How to train neural net to output a 2D polygon?

Lets consider a net, that should map image to an arbitrary four-sided 2D polygon (all vertices are scaled to (0,0) - (1,1)). We need a loss function with a gradient to train it. If we try to use some ...
Dzugaru's user avatar
  • 321
4 votes
0 answers
207 views

Computational geometry vs perceptron for shattering

Given two point sets, $B$ consisting of blue points, and $R$ of red points, on the plane. The problem is to formulate a theoretical model to compare the average runtime of the Computational Geometric ...
PKG's user avatar
  • 461