Jim Cramer has a reputation for getting market calls wrong, but what if you put $1,000 in Inverse Cramer at the start of 2025 ...

Abstract: Inverse problems have many applications in science and engineering. In Computer vision, several image restoration tasks such as inpainting, deblurring, and super-resolution can be formally ...

The inverse Fourier transform (inverse FFT or iFFT) reverses the operation of the Fourier transform and derives a time-domain representation from a frequency-domain dataset. Figure 1. The inverse ...

The initial-boundary and the inverse coefficient problems for the semilinear hyperbolic equation with strong damping are considered in this study. The conditions for the existence and uniqueness of ...

#1 Publication focused exclusively on Interpolation, ie determining value from the existing values in a given data set. #1 Publication focused exclusively on Interpolation, ie determining value from ...

A printer is a wonderful thing when it works, making your life easier by providing lightweight, foldable documents you can tuck in a folder or jam into a pocket. Unfortunately, even the best printers ...

Inverse log, or “antilog,” is the reverse operation of finding a logarithm. If we have a logarithm equation log_b(x) = y, then the inverse log would be b^y = x. Essentially, we’re undoing the ...

This project turns score-based diffusion models into explicit priors for Bayesian inverse problems in imaging. A "score-based prior" allows us to model complex, data-driven posterior distributions ...

Abstract: This paper presents CQT-Diff, a data-driven generative audio model that can, once trained, be used for solving various different audio inverse problems in a problem-agnostic setting.

SCICO is a Python package for solving the inverse problems that arise in scientific imaging applications. Its primary focus is providing methods for solving ill-posed inverse problems by using an ...