Thomas E. Wiese

65 papers receiving 2.2k citations

Thomas E. Wiese's Hit Papers

Learning the MMSE Channel Estimator 2018 · 238 citations
2380+2+5Years since publication50100150200

Peers

Thomas E. Wiese
Comparison fields: 5 of 144
  • Health, Toxicology and Mutagenesis 334
  • Biochemistry 125
  • Pathology and Forensic Medicine 335
  • Genetics 511
  • Toxicology 54
Replace Rob H. Stierum with:
Rob H. Stierum Netherlands
Meirong Xu China
Qian Xie China
Leming M. Shi United States
Daniela Sciaky United States
Yvonne P. Dragan United States
Cheng Xiao China
Srilatha Sakamuru United States
Hisham K. Hamadeh United States
Cynthia A. Afshari United States
Thomas E. Wiese relative to Rob H. Stierum Netherlands Rob H. Stierum's profile →
Citations per field
00.5×2×3×3.7×
Rob H. Stierum · 1×
Citations per year

Countries citing papers authored by Thomas E. Wiese

Since Specialization
Citations

This map shows the geographic impact of Thomas E. Wiese'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 Thomas E. Wiese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas E. Wiese more than expected).

Fields of papers citing papers by Thomas E. Wiese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas E. Wiese. 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 Thomas E. Wiese. The network helps show where Thomas E. Wiese may publish in the future.

Co-authors

The 25 scholars most cited alongside Thomas E. Wiese, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas E. Wiese Line = papers co-authored together Thomas E. Wiese links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning the MMSE Channel Estimator
Hit paper breakdown →
2018238
2 2003204
3 1996183
4 2012131
5 2001108
6 2010102
7 200893
8 201783
9 201677
10 200974
11 199766
12 199257
13 200855
14 199450
15 199349
16 201048
17 201146
18 201444
19 199439
20 201236

About Thomas E. Wiese

Thomas E. Wiese is a scholar working on Genetics, Pathology and Forensic Medicine, Signal Processing, Health, Toxicology and Mutagenesis and Computational Theory and Mathematics, having authored 68 papers that have together received 2.3k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (18 papers), Phytoestrogen effects and research (10 papers), Direction-of-Arrival Estimation Techniques (7 papers), Computational Drug Discovery Methods (5 papers), Microwave Imaging and Scattering Analysis (5 papers), Effects and risks of endocrine disrupting chemicals (5 papers), Sparse and Compressive Sensing Techniques (4 papers) and Advanced MIMO Systems Optimization (4 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (334 citations), Biochemistry (125 citations), Pathology and Forensic Medicine (335 citations), Genetics (511 citations) and Toxicology (54 citations). Thomas E. Wiese has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Wolfgang Utschick, David Neumann, Matthew E. Burow, S.C. Brooks, John A. McLachlan, Steven G. Elliott, Stephen M. Boué, Carol H. Carter‐Wientjes, Thomas E. Cleveland and Melyssa R. Bratton. Their work appears in journals such as Journal of Medicinal Chemistry, Journal of Agricultural and Food Chemistry, IEEE Transactions on Signal Processing, Environmental Health Perspectives and Endocrinology.

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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