Mads Dyrholm

763 total citations
20 papers, 551 citations indexed

About

Mads Dyrholm is a scholar working on Cognitive Neuroscience, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Mads Dyrholm has authored 20 papers receiving a total of 551 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cognitive Neuroscience, 8 papers in Signal Processing and 3 papers in Artificial Intelligence. Recurrent topics in Mads Dyrholm's work include Neural and Behavioral Psychology Studies (10 papers), Visual perception and processing mechanisms (9 papers) and Blind Source Separation Techniques (7 papers). Mads Dyrholm is often cited by papers focused on Neural and Behavioral Psychology Studies (10 papers), Visual perception and processing mechanisms (9 papers) and Blind Source Separation Techniques (7 papers). Mads Dyrholm collaborates with scholars based in Denmark, Germany and United States. Mads Dyrholm's co-authors include Claus Bundesen, Søren Kyllingsbæk, Lucas C. Parra, Thomas Espeseth, Christoforos Christoforou, Lars Kai Hansen, Adam D. Gerson, An Luo, Paul Sajda and Mark J. Wagner and has published in prestigious journals such as NeuroImage, Cerebral Cortex and Neuropsychologia.

In The Last Decade

Mads Dyrholm

20 papers receiving 535 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mads Dyrholm Denmark 10 474 110 37 35 35 20 551
Hubert Banville France 10 285 0.6× 62 0.6× 39 1.1× 30 0.9× 52 1.5× 16 373
Beate Meffert Germany 9 209 0.4× 86 0.8× 30 0.8× 50 1.4× 18 0.5× 37 359
Javad Birjandtalab United States 10 356 0.8× 142 1.3× 27 0.7× 71 2.0× 65 1.9× 23 579
Anne K. Porbadnigk Germany 12 346 0.7× 111 1.0× 35 0.9× 93 2.7× 47 1.3× 20 434
Souvik Phadikar India 11 324 0.7× 130 1.2× 50 1.4× 31 0.9× 87 2.5× 14 444
Mohammad Mikaeili Iran 10 296 0.6× 119 1.1× 27 0.7× 23 0.7× 103 2.9× 26 453
Phattarapong Sawangjai Thailand 6 299 0.6× 76 0.7× 55 1.5× 17 0.5× 43 1.2× 10 402
Vangelis P. Oikonomou Greece 12 313 0.7× 105 1.0× 21 0.6× 16 0.5× 16 0.5× 42 411
Rajdeep Ghosh India 10 262 0.6× 118 1.1× 45 1.2× 18 0.5× 49 1.4× 15 362

Countries citing papers authored by Mads Dyrholm

Since Specialization
Citations

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

Fields of papers citing papers by Mads Dyrholm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mads Dyrholm

This figure shows the co-authorship network connecting the top 25 collaborators of Mads Dyrholm. A scholar is included among the top collaborators of Mads Dyrholm 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 Mads Dyrholm. Mads Dyrholm 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.
Dyrholm, Mads, et al.. (2022). Computationally Efficient Fixed-Filter ANC for Speech Based on Long-Term Prediction for Headphone Applications. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 761–765. 4 indexed citations
2.
Wiegand, Iris, Thomas Töllner, Mads Dyrholm, et al.. (2014). Neural correlates of age-related decline and compensation in visual attention capacity. Neurobiology of Aging. 35(9). 2161–2173. 47 indexed citations
3.
Kraft, Antje, Mads Dyrholm, Christian Kaufmann, et al.. (2014). TMS Over the Right Precuneus Reduces the Bilateral Field Advantage in Visual Short Term Memory Capacity. Brain stimulation. 8(2). 216–223. 22 indexed citations
4.
Espeseth, Thomas, Signe Vangkilde, Anders Petersen, Mads Dyrholm, & Lars T. Westlye. (2014). TVA–based assessment of attentional capacities–associations with age and indices of brain white matter microstructure. Frontiers in Psychology. 5. 1177–1177. 25 indexed citations
5.
Wiegand, Iris, Thomas Töllner, Thomas Habekost, et al.. (2013). Distinct Neural Markers of TVA-Based Visual Processing Speed and Short-Term Storage Capacity Parameters. Cerebral Cortex. 24(8). 1967–1978. 30 indexed citations
6.
Wiegand, Iris, Thomas Töllner, Thomas Habekost, et al.. (2013). FEATURE ARTICLE Distinct Neural Markers of TVA-Based Visual Processing Speed and Short-Term Storage Capacity Parameters. 1 indexed citations
7.
Kraft, Antje, Mads Dyrholm, Claus Bundesen, et al.. (2013). Visual attention capacity parameters covary with hemifield alignment. Neuropsychologia. 51(5). 876–885. 9 indexed citations
8.
Dyrholm, Mads, et al.. (2013). Cortically coupled computer vision with Emotiv headset using distractor variables. 9. 245–250. 6 indexed citations
9.
Dyrholm, Mads, et al.. (2012). Identifying bottom-up and top-down components of attentional weight by experimental analysis and computational modeling.. Journal of Experimental Psychology General. 142(2). 510–535. 40 indexed citations
10.
Gillebert, Céline R., Mads Dyrholm, Signe Vangkilde, et al.. (2012). Attentional priorities and access to short-term memory: Parietal interactions. NeuroImage. 62(3). 1551–1562. 52 indexed citations
11.
Dyrholm, Mads, Søren Kyllingsbæk, Signe Vangkilde, et al.. (2011). Single-Trial Inference on Visual Attention. AIP conference proceedings. 37–43. 1 indexed citations
12.
Dyrholm, Mads, Søren Kyllingsbæk, Thomas Espeseth, & Claus Bundesen. (2011). Generalizing parametric models by introducing trial-by-trial parameter variability: The case of TVA. Journal of Mathematical Psychology. 55(6). 416–429. 97 indexed citations
13.
Parra, Lucas C., Christoforos Christoforou, Adam D. Gerson, et al.. (2008). Spatiotemporal Linear Decoding of Brain State. IEEE Signal Processing Magazine. 25(1). 107–115. 108 indexed citations
14.
Dyrholm, Mads, Christoforos Christoforou, & Lucas C. Parra. (2007). Bilinear Discriminant Component Analysis. Journal of Machine Learning Research. 8(39). 1097–1111. 47 indexed citations
15.
Dyrholm, Mads, Scott Makeig, & Lars Kai Hansen. (2007). Model Selection for Convolutive ICA with an Application to Spatiotemporal Analysis of EEG. Neural Computation. 19(4). 934–955. 39 indexed citations
16.
Dyrholm, Mads & Lars Kai Hansen. (2006). Independent Component Analysis in a convoluted world. 3 indexed citations
17.
Dyrholm, Mads & Lucas C. Parra. (2006). Smooth bilinear classification of EEG. 4249–4252. 8 indexed citations
18.
Dyrholm, Mads, Lars Kai Hansen, Li Wang, Lars Arendt‐Nielsen, & Andrew C. N. Chen. (2004). Convolutive ICA (c-ICA) captures complex spatio-temporal EEG activity. VBN Forskningsportal (Aalborg Universitet). 3 indexed citations
19.
Hansen, Lars Kai & Mads Dyrholm. (2004). A prediction matrix approach to convolutive ICA. 249–258. 7 indexed citations
20.
Pontoppidan, Niels Henrik & Mads Dyrholm. (2003). Fast Monaural Separation of Speech. International Conference on Signal Processing. 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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