Physics informed neural networks for continuum micromechanics

Neural Networks and Micromechanics - ReadingSample

Estimating the continuum of quasars using the articial neural networks

A lot of absorption lines are in the bluewards of Lyα emission line of quasar which is well-known as Lyαforest. Most of absorption lines in this forest belong to the Lyα absorption of the neutral hydrogen in the inter-galactic medium (IGM). For high redshift quasars and in the continuum with low and medium resolution, there are no many regions without absorption, so that, the quasar continuum i...

Deep Jointly-Informed Neural Networks

In this work a novel, automated process for determining an appropriate deep neural network architecture and weight initialization based on decision trees is presented. The method maps a collection of decision trees trained on the data into a collection of initialized neural networks, with the structure of the network determined by the structure of the tree. These models, referred to as “deep jo...

Cytoskeleton Micromechanics: A Continuum-Microscopic Approach

JENNIFER J. YOUNG: Cytoskeleton Micromechanics: A Continuum-Microscopic Approach (Under the direction of Sorin Mitran) Creating accurate, whole-cell scale models of the cytoskeleton is computationally challenging, due to the material’s highly heterogeneous microstructure. Continuumbased models, homogenization methods, and coarse grained models are common modeling approaches. These methods utili...

Physics of Neural Networks

The material basis of our thinking, intelligence and creativity are 1013-1014 nerve cells (neurons) which in our brain are densely packed into a grey sub­ stance weighing about 1.5 kg. Each neuron has — like the root of a tree — highly branched dendrites that collect information from about 10000 other nerve cells. This huge network, which on a microscopic scale looks rather homogeneous and diso...