Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

Genetic algorithms are problem-solving methods that mimic the process of natural selection and can be applied to predicting the movements of security prices.

The author presents a rapidly convergent algorithm to solve the general portfolio problem of maximizing concave utility functions subject to linear constraints. The algorithm is based on an iterative ...

The application of genetic algorithms to the prediction of interfacial structure poses problems not encountered in calculations on bulk crystals or clusters.

moPepGen leverages a graph-based approach to improve the detection of hidden protein variants in a computationally efficient manner.

We compute upper bounds of this critical population size for several examples. We derive several conditions to ensure convergence in the homogeneous case and these provide the first mathematically ...