We present an unsupervised deep-learning approach for the solution of partial differential equations.
The proposed framework is very general, where boundary conditions and other regularizations can be easily integrated
in the loss function. The method is demonstrated on the eigenvalue problem and Electrical Impedance Tomgraphy application.