Chris Donahue

3.2k total citations
13 papers, 176 citations indexed

About

Chris Donahue is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Chris Donahue has authored 13 papers receiving a total of 176 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Signal Processing, 8 papers in Computer Vision and Pattern Recognition and 3 papers in Artificial Intelligence. Recurrent topics in Chris Donahue's work include Music and Audio Processing (9 papers), Music Technology and Sound Studies (5 papers) and Speech and Audio Processing (4 papers). Chris Donahue is often cited by papers focused on Music and Audio Processing (9 papers), Music Technology and Sound Studies (5 papers) and Speech and Audio Processing (4 papers). Chris Donahue collaborates with scholars based in United States, South Korea and United Kingdom. Chris Donahue's co-authors include Miller Puckette, Julian McAuley, Jesse Engel, Nicholas J. Bryan, Shuo Chen, Shinji Watanabe, Kumar Krishna Agrawal, Ishaan Gulrajani, Adam P. Roberts and Matt G. Kushner and has published in prestigious journals such as The Journal of the Acoustical Society of America, Journal of Gambling Studies and IEEE/ACM Transactions on Audio Speech and Language Processing.

In The Last Decade

Chris Donahue

12 papers receiving 169 citations

Peers

Chris Donahue

SP

CVPR

AI

CN

CP

Mahmoud Al Ismail United States

Sanjoy Kumar Saha India

Akhil Raju India

James Whitaker United States

Aitor Álvarez Spain

Finnian Kelly Ireland

Xuan Cao China

Phani Sankar Nidadavolu United States

Claire Pillot-Loiseau France

Mahmoud Al Ismail United States

Chris Donahue

110 ×1.3

SP

59 ×0.7

CVPR

85 ×1.5

AI

12 ×0.5

CN

6 ×0.3

CP

Citations per year, relative to Chris Donahue Chris Donahue (= 1×) peers Mahmoud Al Ismail

Countries citing papers authored by Chris Donahue

Since Specialization

Citations

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

Fields of papers citing papers by Chris Donahue

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chris Donahue

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Lee, Sung-Ju, et al.. (2025). Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations. 1–28. 3 indexed citations

2.

Shi, Jiatong, Hye-jin Shim, Siddhant Arora, et al.. (2025). VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music. 191–209. 1 indexed citations

3.

Su, Kun, Qingqing Huang, Dima Kuzmin, et al.. (2024). V2Meow: Meowing to the Visual Beat via Video-to-Music Generation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 4952–4960. 5 indexed citations

4.

Lindlbauer, David, et al.. (2024). Towards Music-Aware Virtual Assistants. 1–14. 2 indexed citations

5.

Donahue, Chris, et al.. (2024). Music ControlNet: Multiple Time-Varying Controls for Music Generation. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 2692–2703. 15 indexed citations

6.

Lee, Mina, et al.. (2021). Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality. 4362–4379. 8 indexed citations

7.

Engel, Jesse, Kumar Krishna Agrawal, Shuo Chen, et al.. (2019). GANSynth: Adversarial Neural Audio Synthesis. arXiv (Cornell University). 26 indexed citations

8.

Donahue, Chris. (2019). Learning the nuance of musical instrument acoustics. The Journal of the Acoustical Society of America. 146(4_Supplement). 2946–2946.

9.

Donahue, Chris, Julian McAuley, & Miller Puckette. (2018). Synthesizing Audio with GANs.. International Conference on Learning Representations. 11 indexed citations

10.

Donahue, Chris, Julian McAuley, & Miller Puckette. (2018). Adversarial Audio Synthesis. arXiv (Cornell University). 31 indexed citations

11.

Donahue, Chris, Julian McAuley, & Miller Puckette. (2018). Synthesizing Audio with Generative Adversarial Networks. 48 indexed citations

12.

Donahue, Chris, et al.. (2016). Extended Convolution Techniques for Cross-Synthesis.. The Journal of the Abraham Lincoln Association. 3 indexed citations

13.

Kushner, Matt G., et al.. (2007). Urge to Gamble in a Simulated Gambling Environment. Journal of Gambling Studies. 24(2). 219–227. 23 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.

Explore authors with similar magnitude of impact