Reinhard Heckel
- Molecular Biology top 10%
- Artificial Intelligence top 5%
- Mechanical Engineering top 10%
- Computational Theory and Mathematics top 2%
- Biomedical Engineering
- Co-authors
- Robert N. GrassWendelin J. StarkMichela PudduDaniela PăunescuHelmut BölcskeiIlan ShomoronyPhilipp L. AntkowiakMahdi Soltanolkotabi
- Topics
- DNA and Biological Computing (22 papers)Advanced biosensing and bioanalysis techniques (17 papers)Sparse and Compressive Sensing Techniques (11 papers)
- Partner nations
- United StatesGermanySwitzerland
In The Last Decade
Reinhard Heckel
52 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 1.0k
- Artificial Intelligence 331
- Mechanical Engineering 258
- Computational Theory and Mathematics 233
- Biomedical Engineering 215
Countries citing papers authored by Reinhard Heckel
This map shows the geographic impact of Reinhard Heckel'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 Reinhard Heckel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reinhard Heckel more than expected).
Fields of papers citing papers by Reinhard Heckel
This network shows the impact of papers produced by Reinhard Heckel. 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 Reinhard Heckel. The network helps show where Reinhard Heckel may publish in the future.
Co-authorship network of co-authors of Reinhard Heckel
This figure shows the co-authorship network connecting the top 25 collaborators of Reinhard Heckel. A scholar is included among the top collaborators of Reinhard Heckel 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 Reinhard Heckel. Reinhard Heckel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 13 | |
| 4 | 11 | |
| 5 | 5 | |
| 6 | 4 | |
| 7 | 16 | |
| 8 | 112 | |
| 9 | 17 | |
| 10 | 6 | |
| 11 | Measuring Robustness in Deep Learning Based Compressive Sensing | 2 |
| 12 | Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction? | 1 |
| 13 | Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation | 12 |
| 14 | 106 | |
| 15 | Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks | 27 |
| 16 | 6 | |
| 17 | Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior. | 4 |
| 18 | Active Ranking from Pairwise Comparisons and the Futility of Parametric Assumptions. | 2 |
| 19 | Robust Chemical Preservation of Digital Information on DNA in Silica with Error‐Correcting Codesbreakdown → | 485 |
| 20 | 3 |
About Reinhard Heckel
Reinhard Heckel is a scholar working on Structural Biology, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 56 papers that have together received 1.6k indexed citations. Recurring topics across this work include DNA and Biological Computing (22 papers), Advanced biosensing and bioanalysis techniques (17 papers) and Sparse and Compressive Sensing Techniques (11 papers). The work is most often cited by research in Molecular Biology (1.0k citations), Computational Theory and Mathematics (233 citations) and Artificial Intelligence (331 citations). Reinhard Heckel has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Robert N. Grass, Wendelin J. Stark, Michela Puddu, Daniela Păunescu, Helmut Bölcskei, Ilan Shomorony, Philipp L. Antkowiak, Mahdi Soltanolkotabi, Julian Koch and Kannan Ramchandran. Their work appears in journals such as Angewandte Chemie International Edition, Nature Communications and ACS Nano.
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.