Linear inverse problemsNeural networksThe linear inverse problem is fundamental to the development of various scientific areas. Innumerable attempts have been carried out to solve different variants of the linear inverse problem in different applications. Nowadays, the rapid development of deep learning ...
Four such problems are described in detail: deconvolution for acoustic emission, tomographic reconstruction of temperature distribution, electrical-conductivity profiling and inverse scattering. Each exploits a priori information in a different way to mitigate the ill-conditioning inherent in most inverse ...
Turco E. Tools for the numerical solution of inverse problems in structural mechanics: review and research perspectives. Eur J Environ Civ Eng 2016: 1e46. http://dx.doi.org/10.1080/19648189.2015.1134673.Turco, E.: Tools for the numerical solution of inverse problems in structural mechanics: ...
Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to bench...
You might find these chapters and articles relevant to this topic. Chapter Ethical Practice of Research Involving Humans Ethical Clinical Research While historical events have brought to light the need for policies concerning research ethics, the guidance is founded on established norms of research ethic...
[69,70] and should ideally be used alongside alternative ways for children to engage, it was useful for familiarizing CAs with talking about their understandings of critical health literacy and for learning from them how best to introduce critical health literacy as the research topic to children...
After an extensive literature review, reviewing the current state-of-the-art research on the topic, a novel algorithm combining finite element approaches and ML algorithms for transient systems is described. The approach is numerically validated for a one-dimensional system. The overall response is ...
an algorithm that can solve general inverse problems with pre-trained latent diffusion models. Our algorithm incorporates data consistency by solving an optimization problem during the reverse sampling process, a concept that we term as hard data consistency. Upon solving this optim...
As discussed in this previous blog post (discussing a paper on this topic I wrote with some of the members of this collaboration), one reason for this is that the Schrödinger equation can be transformed after some routine calculations to thus making an effective potential for the Schrödinger...
abstract and full text. This technique is susceptible to distortions from differences in personal understanding of concepts, which will lead to the limitation of sample selection. This study is also not a complete and exhaustive consideration of all that has surfaced on this topic over a period ...