Okuda, Neural networks in computational mechanics, Archives of Computational Methods in Engi- neering 3, 4 (1996) 435 - 512.Yagawa G, Okuda H. Neural networks in computational mechanics. Archives of Computationa
Since the deep learning is now a hot topic in computational mechanics with neural networks and many related studies have been reported recently, we discuss here some features of computational mechanics with deep learning. First, similarity and difference
The present paper describes a method to enhance the capability of, or to broaden the scope of computational mechanics by using deep learning, which is one of the machine learning methods and is based on the artificial neural network. The method utilizes deep learning to extract rules inherent in...
A trio of researchers at Ghent University has combined a convolutional neural network with computational neuroscience to create a model that simulates human cochlear mechanics. In their paper published inNature Machine Intelligence,Deepak Baby, Arthur Van Den Broucke and Sarah Verhulst describe how they...
The accuracy of the NNP has recently been further enhanced by employing additional neural networks to construct environment-dependent atomic charges, thereby explicitly accounting for long-range electrostatic interactions23,69. As demonstrated in this work, even for systems with substantial charge transfer...
The integration of deep neural networks with the variational Monte Carlo (VMC) method has marked a substantial advancement in solving the Schrödinger equation. In this work we enforce spin symmetry in the neural-network-based VMC calculation using a modified optimization target. Our method is desi...
Together with the mechanistic ideas discussed below these strategies define the field of “computational chemistry”. The application of quantum mechanics to chemical problems goes back to the end of the 1950s when computers came into use and it was possible to handle very complicated mathematical ...
Fig. 6 Experimental verification of stress design.Andrew J. Lew et al. from the Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology,demonstrated a full workflow to tackle compression design of architected honeycomb materials. They used molecular dynamics ...
Lew et al. from the Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology,demonstrated a full workflow to tackle compression design of architected honeycomb materials. They used molecular dynamics simulations to determine initial insights into the space of ...
The rapid interest in machine learning in general and within computational mechanics is well documented in the scientific literature. By considering the number of publications treating “Artificial Intelligence”, “Machine Learning”, “Deep Learning”, and “Neural Networks”, the interest can be quan...