Mike E. Davies

12.2k total citations · 4 hit papers
181 papers, 7.2k citations indexed

About

Mike E. Davies is a scholar working on Computational Mechanics, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mike E. Davies has authored 181 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Computational Mechanics, 75 papers in Signal Processing and 53 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mike E. Davies's work include Sparse and Compressive Sensing Techniques (76 papers), Blind Source Separation Techniques (58 papers) and Image and Signal Denoising Methods (37 papers). Mike E. Davies is often cited by papers focused on Sparse and Compressive Sensing Techniques (76 papers), Blind Source Separation Techniques (58 papers) and Image and Signal Denoising Methods (37 papers). Mike E. Davies collaborates with scholars based in United Kingdom, France and United States. Mike E. Davies's co-authors include Thomas Blumensath, Mehrdad Yaghoobi, M. Sandler, Chris Duxbury, Laurent Daudet, Juan Pablo Bello, Rémi Gribonval, Christopher J. James, Yonina C. Eldar and SA Abdallah and has published in prestigious journals such as The Lancet, Proceedings of the IEEE and Scientific Reports.

In The Last Decade

Mike E. Davies

172 papers receiving 6.8k citations

Hit Papers

Iterative hard thresholding for compressed sensing 2005 2026 2012 2019 2009 2008 2005 2010 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mike E. Davies United Kingdom 35 3.9k 2.6k 2.3k 1.8k 774 181 7.2k
Thomas Blumensath United Kingdom 24 3.9k 1.0× 1.5k 0.6× 1.6k 0.7× 2.0k 1.1× 912 1.2× 70 6.0k
Justin Romberg United States 25 4.2k 1.1× 1.4k 0.5× 2.4k 1.0× 2.0k 1.1× 1.3k 1.7× 138 7.4k
Zhifeng Zhang China 10 2.6k 0.7× 1.8k 0.7× 2.4k 1.0× 1.0k 0.6× 913 1.2× 43 6.8k
Trac D. Tran United States 39 2.2k 0.6× 1.7k 0.6× 3.1k 1.3× 1.4k 0.8× 1.0k 1.3× 265 7.2k
Rémi Gribonval France 40 3.9k 1.0× 4.5k 1.7× 2.2k 0.9× 965 0.5× 528 0.7× 168 8.5k
Gonzalo R. Arce United States 52 2.6k 0.7× 1.4k 0.5× 4.2k 1.8× 2.4k 1.3× 2.0k 2.6× 413 9.2k
Michal Aharon Israel 10 4.1k 1.1× 1.7k 0.7× 7.4k 3.2× 1.6k 0.9× 572 0.7× 17 11.1k
Mark A. Davenport United States 27 4.9k 1.3× 1.7k 0.7× 1.8k 0.8× 2.8k 1.5× 1.6k 2.1× 82 7.9k
James H. McClellan United States 39 2.0k 0.5× 3.0k 1.1× 1.7k 0.7× 1.4k 0.8× 1.3k 1.7× 282 7.0k
Arvind Ganesh India 19 4.8k 1.2× 2.4k 0.9× 7.7k 3.3× 1.3k 0.7× 906 1.2× 43 11.9k

Countries citing papers authored by Mike E. Davies

Since Specialization
Citations

This map shows the geographic impact of Mike E. Davies's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mike E. Davies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mike E. Davies more than expected).

Fields of papers citing papers by Mike E. Davies

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mike E. Davies. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mike E. Davies. The network helps show where Mike E. Davies may publish in the future.

Co-authorship network of co-authors of Mike E. Davies

This figure shows the co-authorship network connecting the top 25 collaborators of Mike E. Davies. A scholar is included among the top collaborators of Mike E. Davies based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mike E. Davies. Mike E. Davies is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Sheehan, Michael P., Julián Tachella, & Mike E. Davies. (2024). Spline Sketches: An Efficient Approach for Photon Counting Lidar. IEEE Transactions on Computational Imaging. 10. 863–875. 3 indexed citations
2.
Chen, Dongdong, et al.. (2023). Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning. IEEE Signal Processing Magazine. 40(1). 134–147. 16 indexed citations
3.
Sun, Mengwei, Mike E. Davies, Ian K. Proudler, & James R. Hopgood. (2022). Adaptive Kernel Kalman Filter Based Belief Propagation Algorithm for Maneuvering Multi-Target Tracking. IEEE Signal Processing Letters. 29. 1452–1456. 16 indexed citations
4.
Davies, Mike E., et al.. (2021). Staggered Coprime Pulse Repetition Frequencies Synthetic Aperture Radar (SCopSAR). IEEE Transactions on Geoscience and Remote Sensing. 60. 1–11. 7 indexed citations
5.
Chen, Dongdong, et al.. (2021). Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography. IEEE Transactions on Medical Imaging. 41(1). 3–13. 58 indexed citations
6.
Fang, Ming, Angela Di Fulvio, Stephen McLaughlin, et al.. (2021). Bayesian Activity Estimation and Uncertainty Quantification of Spent Nuclear Fuel Using Passive Gamma Emission Tomography. Journal of Imaging. 7(10). 212–212. 3 indexed citations
7.
Tachella, Julián, Junqi Tang, & Mike E. Davies. (2020). CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser.. arXiv (Cornell University). 1 indexed citations
8.
Tang, Junqi, Karen Egiazarian, Mohammad Golbabaee, & Mike E. Davies. (2020). The Practicality of Stochastic Optimization in Imaging Inverse Problems. IEEE Transactions on Computational Imaging. 6. 1471–1485. 14 indexed citations
9.
Davies, Mike E., et al.. (2020). ($\ell _1,\ell _2$)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements. IEEE Signal Processing Letters. 27. 396–400. 4 indexed citations
10.
Chen, Dongdong, Mohammad Golbabaee, Pedro A. Gómez, Marion I. Menzel, & Mike E. Davies. (2019). Deep Fully Convolutional Network for MR Fingerprinting. Edinburgh Research Explorer. 1 indexed citations
11.
Perelli, Alessandro, et al.. (2018). Quantitative cone-beam CT reconstruction with polyenergetic scatter model fusion. Physics in Medicine and Biology. 63(22). 225001–225001. 4 indexed citations
12.
Golbabaee, Mohammad & Mike E. Davies. (2018). Inexact Gradient Projection and Fast Data Driven Compressed Sensing. IEEE Transactions on Information Theory. 64(10). 6707–6721. 9 indexed citations
13.
Golbabaee, Mohammad, Dongdong Chen, Pedro A. Gómez, Marion I. Menzel, & Mike E. Davies. (2018). A deep learning approach for Magnetic Resonance Fingerprinting.. arXiv (Cornell University). 1 indexed citations
14.
Perelli, Alessandro, et al.. (2018). Performance Analysis of Approximate Message Passing for Distributed Compressed Sensing. IEEE Journal of Selected Topics in Signal Processing. 12(5). 857–870. 15 indexed citations
15.
Perelli, Alessandro, et al.. (2017). Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source. Physics in Medicine and Biology. 62(22). 8739–8762. 2 indexed citations
16.
Puy, Gilles, Mike E. Davies, & Rémi Gribonval. (2017). Recipes for Stable Linear Embeddings From Hilbert Spaces to $ {\mathbb {R}}^{m}$. IEEE Transactions on Information Theory. 63(4). 2171–2187. 7 indexed citations
17.
Cevher, Volkan, et al.. (2011). Compressible Priors for High-dimensional Statistics. arXiv (Cornell University). 4 indexed citations
18.
Blumensath, Thomas & Mike E. Davies. (2007). Blind Separation of Maternal and Fetal ECG Recordings using Adaptive Sparse Representations. ePrints Soton (University of Southampton). 1 indexed citations
19.
Davies, Mike E. & Laurent Daudet. (2004). Fast sparse subband decomposition using FIRSP. European Signal Processing Conference. 1665–1668. 4 indexed citations
20.
Davies, Mike E., et al.. (1987). A Unified Lunar Control Network - The Nearside. Bulletin of the American Astronomical Society. 19. 872. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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