William Beluch

873 total citations · 1 hit paper
9 papers, 435 citations indexed

About

William Beluch is a scholar working on Artificial Intelligence, Aerospace Engineering and Paleontology. According to data from OpenAlex, William Beluch has authored 9 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Aerospace Engineering and 1 paper in Paleontology. Recurrent topics in William Beluch's work include Adversarial Robustness in Machine Learning (5 papers), Advanced SAR Imaging Techniques (2 papers) and Imbalanced Data Classification Techniques (2 papers). William Beluch is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Advanced SAR Imaging Techniques (2 papers) and Imbalanced Data Classification Techniques (2 papers). William Beluch collaborates with scholars based in Germany, India and Austria. William Beluch's co-authors include Jan M. Köhler, Tim Genewein, Andreas Nürnberger, Michael Pfeiffer, Bin Yang, Dan Zhang, Campbell Rolian, Yingguang Frank Chan, Marek Kučka and John Cobb and has published in prestigious journals such as eLife, G3 Genes Genomes Genetics and Open access LMU (Ludwid Maxmilian's Universitat Munchen).

In The Last Decade

William Beluch

9 papers receiving 420 citations

Hit Papers

The Power of Ensembles for Active Learning in Image Class... 2018 2026 2020 2023 2018 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The Power of Ensembles for Active Learning in Image Classification
    2018 336 citations William Beluch, Tim Genewein et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William Beluch Germany 6 262 130 43 33 31 9 435
Zhihong Chen China 10 369 1.4× 297 2.3× 42 1.0× 16 0.5× 15 0.5× 30 613
Deepak Pathak South Korea 10 209 0.8× 345 2.7× 42 1.0× 55 1.7× 20 0.6× 29 663
Shiyu Li China 11 150 0.6× 144 1.1× 22 0.5× 22 0.7× 15 0.5× 49 406
Raid Rafi Omar Al-Nima Iraq 13 97 0.4× 177 1.4× 33 0.8× 20 0.6× 10 0.3× 59 468
M. Rahmat Widyanto Indonesia 12 107 0.4× 181 1.4× 28 0.7× 23 0.7× 8 0.3× 44 364
Inam Ullah China 13 149 0.6× 228 1.8× 62 1.4× 12 0.4× 8 0.3× 49 503
Madhuri S. Joshi India 9 98 0.4× 145 1.1× 64 1.5× 30 0.9× 10 0.3× 33 452
Andrei Stoian France 7 254 1.0× 172 1.3× 25 0.6× 10 0.3× 18 0.6× 16 482

Countries citing papers authored by William Beluch

Since Specialization
Citations

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

Fields of papers citing papers by William Beluch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William Beluch. 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 William Beluch. The network helps show where William Beluch may publish in the future.

Co-authorship network of co-authors of William Beluch

This figure shows the co-authorship network connecting the top 25 collaborators of William Beluch. A scholar is included among the top collaborators of William Beluch 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 William Beluch. William Beluch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Zhang, Dan, et al.. (2023). Anomaly-Aware Semantic Segmentation via Style-Aligned OoD Augmentation. 4067–4075. 3 indexed citations
2.
Beluch, William, et al.. (2023). A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing. Open access LMU (Ludwid Maxmilian's Universitat Munchen). 523–540. 12 indexed citations
3.
4.
Beluch, William, et al.. (2021). Independent evolution toward larger body size in the distinctive Faroe Island mice. G3 Genes Genomes Genetics. 11(1). 2 indexed citations
5.
Beluch, William, et al.. (2021). Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning. International Conference on Learning Representations. 8 indexed citations
6.
Beluch, William, et al.. (2021). On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration. 8029–8036. 12 indexed citations
7.
Beluch, William, et al.. (2021). Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra. 1–6. 5 indexed citations
8.
Kučka, Marek, William Beluch, Ronald Naumann, et al.. (2019). An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice. eLife. 8. 51 indexed citations
9.
Beluch, William, Tim Genewein, Andreas Nürnberger, & Jan M. Köhler. (2018). The Power of Ensembles for Active Learning in Image Classification. 9368–9377. 336 indexed citations breakdown →

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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