4 papers
Residual Random Neural Networks
M. Andrecut
The single-layer feedforward neural network with random weights is a recurring motif in the neural networks literature. The advantage of these networks is their simplified training…
Heuristic Optimal Transport in Branching Networks
M. Andrecut
Optimal transport aims to learn a mapping of sources to targets by minimizing the cost, which is typically defined as a function of distance. The solution to this problem consists…
ELM Ridge Regression Boosting
M. Andrecut
We discuss a boosting approach for the Ridge Regression (RR) method, with applications to the Extreme Learning Machine (ELM), and we show that the proposed method significantly imp…
TensorFlow Chaotic Prediction and Blow Up
M. Andrecut
Predicting the dynamics of chaotic systems is one of the most challenging tasks for neural networks, and machine learning in general. Here we aim to predict the spatiotemporal chao…