Tag Disordered Systems and Neural Networks
In the world of deep learning, researchers are constantly striving to develop models that can accurately classify and analyze complex datasets. In pursuit of this goal, a team of talented individuals including Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron… Continue Reading →
Large feedforward neural networks have become increasingly popular over the years due to their ability to learn complex patterns and make accurate predictions. However, a common challenge with these networks is their poor performance on test data, a phenomenon known… Continue Reading →
The study conducted by Ludovic Berthier, Hugo Jacquin, and Francesco Zamponi explores the jamming transition of harmonic spheres, providing valuable insights into the phase behavior and correlation functions of dense assemblies of soft repulsive particles. This research is applicable to… Continue Reading →