Jerret Ross

624 total citations · 1 hit paper
10 papers, 250 citations indexed

About

Jerret Ross is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Jerret Ross has authored 10 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Jerret Ross's work include Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers) and Robotic Path Planning Algorithms (2 papers). Jerret Ross is often cited by papers focused on Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers) and Robotic Path Planning Algorithms (2 papers). Jerret Ross collaborates with scholars based in United States, Switzerland and Brazil. Jerret Ross's co-authors include Youssef Mroueh, Payel Das, Brian Belgodere, Inkit Padhi, Vijil Chenthamarakshan, Igor Melnyk, Tom Sercu, Xiaodong Cui, Wei Zhang and Tianbao Yang and has published in prestigious journals such as Nature Machine Intelligence, IEEE Journal on Emerging and Selected Topics in Circuits and Systems and arXiv (Cornell University).

In The Last Decade

Jerret Ross

7 papers receiving 242 citations

Hit Papers

Large-scale chemical language representations capture mol... 2022 2026 2023 2024 2022 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jerret Ross United States 4 147 126 104 46 14 10 250
Brian Belgodere United States 5 144 1.0× 126 1.0× 105 1.0× 52 1.1× 27 1.9× 7 289
Jiacheng Xiong China 6 152 1.0× 112 0.9× 102 1.0× 47 1.0× 12 0.9× 10 273
Łukasz Maziarka Poland 5 147 1.0× 117 0.9× 105 1.0× 27 0.6× 17 1.2× 11 213
Yuzhi Guo United States 6 218 1.5× 188 1.5× 208 2.0× 62 1.3× 17 1.2× 20 346
Tomasz Danel Poland 8 191 1.3× 139 1.1× 142 1.4× 32 0.7× 19 1.4× 16 304
Shoichi Ishida Japan 9 141 1.0× 132 1.0× 162 1.6× 63 1.4× 11 0.8× 23 339
Zhichun Guo United States 8 90 0.6× 99 0.8× 63 0.6× 87 1.9× 24 1.7× 12 251
Seongok Ryu South Korea 6 295 2.0× 204 1.6× 253 2.4× 44 1.0× 18 1.3× 9 428
Chao Pang China 5 70 0.5× 64 0.5× 66 0.6× 83 1.8× 22 1.6× 6 205

Countries citing papers authored by Jerret Ross

Since Specialization
Citations

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

Fields of papers citing papers by Jerret Ross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jerret Ross

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

All Works

10 of 10 papers shown
1.
Ross, Jerret, Brian Belgodere, Samuel C. Hoffman, et al.. (2025). GP-MoLFormer: a foundation model for molecular generation. Digital Discovery. 4(10). 2684–2696. 3 indexed citations
2.
Belgodere, Brian, Igor Melnyk, Youssef Mroueh, et al.. (2024). Auditing and Generating Synthetic Data with Controllable Trust Trade-offs. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 1–1. 4 indexed citations
3.
Ross, Jerret, Brian Belgodere, Vijil Chenthamarakshan, et al.. (2022). Large-scale chemical language representations capture molecular structure and properties. Nature Machine Intelligence. 4(12). 1256–1264. 227 indexed citations breakdown →
4.
Melnyk, Igor, et al.. (2019). Improved Adversarial Image Captioning. International Conference on Learning Representations. 1 indexed citations
5.
Liu, Mingrui, Youssef Mroueh, Jerret Ross, et al.. (2019). Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets. arXiv (Cornell University). 5 indexed citations
6.
Melnyk, Igor, et al.. (2019). Wasserstein Barycenter Model Ensembling. arXiv (Cornell University). 3 indexed citations
7.
Melnyk, Igor, et al.. (2018). Improved Image Captioning with Adversarial Semantic Alignment.. arXiv (Cornell University). 6 indexed citations
8.
Blank, Douglas & Jerret Ross. (1997). Learning in a fuzzy logic robot controller. Scholarship, Research, and Creative Work at Bryn Mawr College (Bryn Mawr College). 778–778.
9.
Blank, Douglas & Jerret Ross. (1997). Incorporating a Connectionist Vision Module into a Fuzzy, Behavior-Based Robot Controller. Scholarship, Research, and Creative Work at Bryn Mawr College (Bryn Mawr College). 1 indexed citations
10.
Owens, Robyn, et al.. (1993). JPEG and Image Measures. UWA Profiles and Research Repository (University of Western Australia). 14–14.

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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