Latest Articles for Inverse Problems

New methods improve data analysis with incomplete information.

This article explores solving inverse problems using advanced models and techniques.

New methods improve accuracy and efficiency in solving inverse problems.

New regularization method improves heart electrical activity reconstructions from body surface measurements.

This article examines methods for assessing corrosion in buried objects without excavation.

A novel approach combines domain decomposition and artificial neural networks for complex problem solving.

A new method improves image reconstruction in noisy medical data.

Exploring the Unique Continuation Principle's impact on wave behavior in conductive materials.

A new method improves parameter estimates in inverse problems affected by noise.

Exploring the integration of deep learning with Bayesian methods to improve data estimation.

This article discusses modeling techniques for analyzing tumor growth and early detection.

Optimizing data selection methods for solving inverse problems in science and engineering.

Exploring the fascinating world of AGN and their jets.

ProxSkip speeds up image processing in inverse problems while maintaining quality.

Ensemble Kalman Diffusion Guidance offers a fresh approach to solving complex inverse problems.

A new method blends numerical techniques with neural networks for solving complex equations.

A deep dive into biharmonic operators and their role in inverse problems.

Discover how PINNs improve predictions in electrical circuit analysis.

Combining techniques for better accuracy in predicting mechanical properties of materials.

Discover how bilevel optimization tackles complex inverse problems efficiently.

A study on handling errors in inverse problems affected by noise.

Explore how RFMs transform image generation in creative fields.

Discover how Measurement Optimization transforms image processing for clearer results.

Explore how fractional diffusion equations explain complex particle movements.

DAWN-SI enhances solutions to inverse problems by addressing noise and uncertainty.

A look into the behavior and applications of coupled harmonic oscillators.

Using AI to tackle challenges in designing anisotropic materials.

Learn how optimal transport impacts logistics, data science, and everyday applications.

Discover the significance of the fractional Helmholtz equation in wave behavior.

New method improves results in solving complex inverse problems using diffusion models.

Neural networks restore clarity in challenging inverse problems across various fields.

Discover how Carleman weight functions help manage complex systems effectively.

CA-DPS brings new hope for solving inverse problems in imaging.