Related papers: Gravix: Active Learning for Gravitational Waves Cl…

We study the problem of semi-supervised learning with Graph Neural Networks (GNNs) in an active learning setup. We propose GraphPart, a novel partition-based active learning approach for GNNs. GraphPart first splits the graph into disjoint…

This version withdrawn by arXiv administrators because the author did not have the right to agree to our license at the time of submission.

Using the Einstein gravitation theory we show how to obtain the basic equations which predict the gravitational waves. This paper was written to graduate and post-graduate students of Physics. We deduce the equations didactically following…

This paper has been withdrawn by the author.

This manuscript has been withdrawn due to less meaning.

Deep learning method develops very fast as a tool for data analysis these years. Such a technique is quite promising to treat gravitational wave detection data. There are many works already in the literature which used deep learning…

This paper has been removed by arXiv administrators because it overlaps gr-qc/0102077 and others. This paper also has excessive overlap with the following papers also written by the authors or their collaborators: gr-qc/0603027,…

This is the original version of my Ph.D. thesis. The main results have been divided up between papers arXiv:2111.09784 and arXiv:2204.10924. This paper has been kept on the arXiv to preserve some proofs of elementary lemmas that will be…

Lecture notes on selected topics in the theory of gravitation.

This paper has been withdrawn by the author due to rewritting and skipping crucial sign errors.

This paper has been withdrawn.

This article has been withdrawn by arXiv administrators because the submitter did not have the legal authority to grant the license applied to the work.

The paper is withdrawn by the authors and replaced be an improved and extended version arxiv: 0812.2968

Gravitational-wave data analysis is rapidly absorbing techniques from deep learning, with a focus on convolutional networks and related methods that treat noisy time series as images. We pursue an alternative approach, in which waveforms…

Gravitational wave astronomy is rapidly advancing with the development of new observatories, leading to an increasing volume and complexity of data. This trend places growing pressure on classical data analysis methods and motivates the…

The paper has been withdrawn.

GGR News: -we hear that..., by David Garfinkle -Network of gravitational-wave detectors, by Stan Whitcomb Research Briefs: -New tests of general relativity, by Quentin Bailey Conference Reports: -Theory meets data analysis, by Steve…

We present a novel machine-learning approach to estimate selection effects in gravitational-wave observations. Using techniques similar to those commonly employed in image classification and pattern recognition, we train a series of…

This paper has been withdrawn by the author due to a error in attachment of source file.

In this paper, we review the theoretical basis for generation of gravitational waves and the detection techniques used to detect a gravitational wave. To materialize this goal in a thorough way we first start with a mathematical background…