Marc Goodfellow

2.4k citations
55 papers · 1.5k · h-index 23

Impact in

Papers in

Marc Goodfellow

53 papers receiving 1.5k citations

Peers

Marc Goodfellow
Comparison fields: 5 of 107
  • Cognitive Neuroscience 1.0k
  • Cellular and Molecular Neuroscience 342
  • Psychiatry and Mental health 197
  • Statistical and Nonlinear Physics 166
  • Radiology, Nuclear Medicine and Imaging 112
Replace Yujiang Wang with:
Yujiang Wang United Kingdom
J.P. Pijn Netherlands
Demetrios N. Velis Netherlands
Sarah F. Muldoon United States
László Négyessy Hungary
Jean‐Philippe Thivierge Canada
Peter N. Taylor United Kingdom
S. Clémenceau France
Berj L. Bardakjian Canada
Annika Lüttjohann Germany
Marc Goodfellow relative to Yujiang Wang United Kingdom Yujiang Wang's profile →
Citations per field
00.5×1.5×
Yujiang Wang · 1×
Citations per year

Countries citing papers authored by Marc Goodfellow

Since Specialization
Citations

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

Fields of papers citing papers by Marc Goodfellow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marc Goodfellow, 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 Marc Goodfellow Line = papers co-authored together Marc Goodfellow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016118
2 2020107
3 201488
4 201185
5 201763
6 201462
7 201157
8 201250
9 201648
10 201647
11 201245
12 201444
13 201440
14 201237
15 201634
16 201929
17 201627
18 201227
19 201925
20 201225

About Marc Goodfellow

Marc Goodfellow is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Cellular and Molecular Neuroscience, Molecular Biology and Artificial Intelligence, having authored 55 papers that have together received 1.5k indexed citations. Recurring topics across this work include Neural dynamics and brain function (28 papers), Functional Brain Connectivity Studies (28 papers), EEG and Brain-Computer Interfaces (13 papers), stochastic dynamics and bifurcation (8 papers), Neuroscience and Neuropharmacology Research (6 papers), Gene Regulatory Network Analysis (5 papers), Advanced Neuroimaging Techniques and Applications (4 papers) and Gaussian Processes and Bayesian Inference (4 papers). The work is most often cited by research in Cognitive Neuroscience (1.0k citations), Cellular and Molecular Neuroscience (342 citations), Psychiatry and Mental health (197 citations), Statistical and Nonlinear Physics (166 citations) and Radiology, Nuclear Medicine and Imaging (112 citations). Marc Goodfellow has collaborated with scholars based in United Kingdom, Switzerland and Germany. Frequent co-authors include Gerold Baier, Kaspar Schindler, John R. Terry, Mark P. Richardson, Peter N. Taylor, Yujiang Wang, Christian Rummel, Eugenio Abela, Marinho A. Lopes and Luke Tait. Their work appears in journals such as PLoS Computational Biology, Scientific Reports, Frontiers in Neurology, NeuroImage and Clinical Neurophysiology.

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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