Aaron Adcock

551 total citations
10 papers, 248 citations indexed

About

Aaron Adcock is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Aaron Adcock has authored 10 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Aaron Adcock's work include Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Advanced Graph Theory Research (2 papers). Aaron Adcock is often cited by papers focused on Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Advanced Graph Theory Research (2 papers). Aaron Adcock collaborates with scholars based in United States, Israel and Germany. Aaron Adcock's co-authors include Blair D. Sullivan, Michael W. Mahoney, Gunnar Carlsson, Daniel L. Rubin, Ross Girshick, Piotr Dollár, Laura Gustafson, Mannat Singh, Laurens van der Maaten and Dhruv Mahajan and has published in prestigious journals such as Computer Vision and Image Understanding, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Journal of Information Processing.

In The Last Decade

Aaron Adcock

10 papers receiving 233 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aaron Adcock United States	8	100	89	61	32	28	10	248
Ambedkar Dukkipati India	10	136 1.4×	88 1.0×	32 0.5×	100 3.1×	42 1.5×	43	337
Yunlong He United States	4	89 0.9×	77 0.9×	50 0.8×	25 0.8×	8 0.3×	6	276
Thanh‐Nghi Do Vietnam	8	135 1.4×	181 2.0×	18 0.3×	50 1.6×	8 0.3×	35	299
Ashish Negi India	12	41 0.4×	103 1.2×	50 0.8×	100 3.1×	20 0.7×	41	339
Avanti Athreya United States	7	88 0.9×	21 0.2×	28 0.5×	126 3.9×	20 0.7×	16	243
Kazuho Watanabe Japan	9	155 1.6×	61 0.7×	13 0.2×	16 0.5×	7 0.3×	53	251
Soledad Villar United States	7	73 0.7×	59 0.7×	21 0.3×	13 0.4×	3 0.1×	14	182
Bo Chang Canada	7	99 1.0×	47 0.5×	29 0.5×	41 1.3×	4 0.1×	15	241
Federico Errica Italy	6	182 1.8×	49 0.6×	37 0.6×	43 1.3×	7 0.3×	17	322

Countries citing papers authored by Aaron Adcock

Since Specialization

Citations

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

Fields of papers citing papers by Aaron Adcock

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaron Adcock

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

All Works

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10 of 10 papers shown

1.

Singh, Mannat, Quentin Duval, Kalyan Vasudev Alwala, et al.. (2023). The effectiveness of MAE pre-pretraining for billion-scale pretraining. 5461–5471. 14 indexed citations

2.

Gustafson, Laura, et al.. (2023). Vision-Language Models Performing Zero-Shot Tasks Exhibit Disparities Between Gender Groups. 2770–2777. 2 indexed citations

3.

Gustafson, Laura, Nikhila Ravi, Quentin Duval, et al.. (2023). FACET: Fairness in Computer Vision Evaluation Benchmark. 20313–20325. 9 indexed citations

4.

Singh, Mannat, Laura Gustafson, Aaron Adcock, et al.. (2022). Revisiting Weakly Supervised Pre-Training of Visual Perception Models. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 794–804. 44 indexed citations

5.

Fan, Haoqi, Tullie Murrell, Heng Wang, et al.. (2021). PyTorchVideo. 3783–3786. 28 indexed citations

6.

Karrer, Brian, et al.. (2016). Social Hash: an assignment framework for optimizing distributed systems operations on social networks. 455–468. 19 indexed citations

7.

Adcock, Aaron, et al.. (2015). Zig-Zag Numberlink is NP-Complete. Journal of Information Processing. 23(3). 239–245. 12 indexed citations

8.

Adcock, Aaron, Daniel L. Rubin, & Gunnar Carlsson. (2014). Classification of hepatic lesions using the matching metric. Computer Vision and Image Understanding. 121. 36–42. 54 indexed citations

9.

Adcock, Aaron, Blair D. Sullivan, & Michael W. Mahoney. (2013). Tree-Like Structure in Large Social and Information Networks. 1–10. 64 indexed citations

10.

Brown, Charles G., Aaron Adcock, S.G. Azevedo, J. Liebman, & E. Bond. (2011). Adaptation of a cubic smoothing spline algorithm for multi-channel data stitching at the National Ignition Facility. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7916. 79160P–79160P. 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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