Differential Equations and Inverse Problems
Deadline for manuscript submissions: 28 August 2024 | Viewed by 5118
2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Interests: inverse and ill-posed problems; partial differential equations; mathematical physics; financial mathematics; mathematical imaging; artificial intelligence; deep learning; reinforcement learning; multiscale methods; homotopy methods
Interests: structure-preserving algorithms for differential equations; numerical methods for stochastic differential equation
Interests: ill-posed problems; regularization method; inverse source problems; backward problems; parabolic equation; elliptic equation; fractional diffusion equation; convergence analysis
Differential equations and inverse problems have become a rapidly growing topic because of the new techniques developed recently and amazing achievements in computational sciences. With the progress of science and technology, differential equations and inverse problems have quickly developed, and new waves have been successively set off in a broad range of disciplines, such as mathematics, physics, engineering, business, economics, earth science, biology, etc.
The purpose of this Special Issue is to gather contributions from experts on the theory and numerical aspects of differential equations and inverse problems, including but not limited to differential equations and fractional differential equations, initial value problems and related inverse problems, boundary value problems and related inverse problems, inverse problems in imaging, image reconstruction in tomography, stability analysis, regularization methods, novel numerical algorithms (such as multigrid methods, wavelet methods, homotopy methods, structure-preserving methods), and artificial intelligence (such as deep learning, reinforcement learning). Moreover, we encourage submissions of their applications in various practical areas.
Dr. Tao Liu
Dr. Qiang Ma
Dr. Songshu Liu
Manuscript Submission Information
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- partial differential equations
- ordinary differential equations
- stochastic differential equations
- fractional differential equations
- fractional calculus
- inverse and ill-posed problems
- image reconstruction
- tomographic reconstruction
- regularization methods
- numerical methods
- structure-preserving methods
- artificial intelligence
- deep learning
- reinforcement learning