Convergence Results for Neural Networks via Electrodynamics
We study whether a depth two neural network can learn another depth two network using gradient descent. Assuming a linear output node, we show that the question of whether gradi...
We study whether a depth two neural network can learn another depth two network using gradient descent. Assuming a linear output node, we show that the question of whether gradi...
We introduce a new iterative regularization procedure for inverse problems based on the use of Bregman distances, with particular focus on problems arising in image processing. ...
In recent years observations at the level of individual atoms and molecules became possible by microscopy and spectroscopy. Imaging of single fluorescence molecules has been ach...
Abstract We report on solution‐processed hybrid solar cells consisting of a nanocrystalline inorganic semiconductor, CuInS 2 , and organic materials. Synthesis of quantized CuIn...
A method is proposed that allows for a more precise evaluation of the spin splitting of electronic levels induced by the exchange interaction between effective-mass electrons an...