Truncated Neural Networks?

Recently, I’ve found good success in truncated neural networks ie functions of the form $$ g=f1_{[-M,M]^d}, $$ where $f:\mathbb{R}^d\to\mathbb{R}^n$ is a feed-forward neural network and $1_{[-M,M]^d}$ is the indicator function on the cube of radius $M>0$. Has anyone come across any paper using these “truncated neural networks” instead of simply using (un-truncated/classical) feed-forward neural networks?

Different formula of Cross-Entropy in Pytorch

In my understanding, to calculate Cross-Entropy is using this formula: $$ H(p,q) = – \sum p_i \log(q_i) $$ But in Pytorch nn.CrossEntropyLoss is calculated using this formula: $$ loss = -\log\left( \frac{\exp(x[class])}{\sum_j \exp(x_j)} \right) $$ that I think it only addresses the $\log(q_i)$ part in the first formula. So is that means Pytorch using different…

Intelligent crossover for binary chromosomes

I’m studying about genetic algorithm. I’m studying about different crossover operations used for binary chromosomes. These methods usually don’t use any intelligence (1-point crossover, uniform crossover, etc.). I found methods like Fitness-based Crossover and Boltzmann Crossover, which use fitness value so that the child will be created from better parents with a better probability. So…

Training dataset for convolutional neural network classification – will images captured on the ground be useful for training aerial imagery?

I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs). The basic idea that I am wanting to get into involves separating crops from weeds from aerial imagery (either captured by drones or piloted aircraft). The idea of the project that I am proposing involves spending some time…

word2vec implementation in Tensorflow 2.0

I want to implement word2vec using tensorflow 2.0 I have prepared dataset according to the skip-gramm model and I have got approx. 18 million observations(target and context words). I have used the followng dataset for my goal: https://www.kaggle.com/c/quora-question-pairs/notebooks I have created a new dataset for n-gramm model. I have used windows_size 2 and number of…