Aaron Defazio

3.3k total citations
12 papers, 167 citations indexed

About

Aaron Defazio is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Aaron Defazio has authored 12 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Biomedical Engineering. Recurrent topics in Aaron Defazio's work include Medical Imaging Techniques and Applications (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). Aaron Defazio is often cited by papers focused on Medical Imaging Techniques and Applications (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). Aaron Defazio collaborates with scholars based in United States, Australia and Israel. Aaron Defazio's co-authors include Tullie Murrell, Anuroop Sriram, C. Lawrence Zitnick, Michael Rabbat, Florian Knöll, Jure Žbontar, Matthew J. Muckley, Michael P. Recht, Nafissa Yakubova and Daniel K. Sodickson and has published in prestigious journals such as Magnetic Resonance in Medicine, Neural Computing and Applications and ANU Open Research (Australian National University).

In The Last Decade

Aaron Defazio

10 papers receiving 165 citations

Peers

Aaron Defazio
Tullie Murrell United States
Hyungseob Shin South Korea
Elizabeth K. Cole United States
Mika Pollari Finland
Yunlu Yan China
Yılmaz Korkmaz Türkiye
Yinzhe Wu United Kingdom
Xiong Zhao China
Tullie Murrell United States
Aaron Defazio
Citations per year, relative to Aaron Defazio Aaron Defazio (= 1×) peers Tullie Murrell

Countries citing papers authored by Aaron Defazio

Since Specialization
Citations

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

Fields of papers citing papers by Aaron Defazio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaron Defazio

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

All Works

12 of 12 papers shown
1.
Cutkosky, Ashok, et al.. (2024). The Road Less Scheduled. 9974–10007.
2.
Defazio, Aaron, et al.. (2024). Directional Smoothness and Gradient Methods: Convergence and Adaptivity. 14810–14848. 1 indexed citations
3.
Defazio, Aaron & Léon Bottou. (2022). A scaling calculus for the design and initialization of ReLU networks. Neural Computing and Applications. 34(17). 14807–14821.
4.
Defazio, Aaron, Mark Tygert, Rachel Ward, & Jure Žbontar. (2021). Compressed sensing with a jackknife and a bootstrap. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
5.
Defazio, Aaron, Mark Tygert, Rachel Ward, & Jure Žbontar. (2021). Compressed sensing with a jackknife, a bootstrap, and visualization. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
6.
Defazio, Aaron, Tullie Murrell, & Michael P. Recht. (2020). MRI Banding Removal via Adversarial Training. Neural Information Processing Systems. 33. 7660–7670. 1 indexed citations
7.
Knöll, Florian, Tullie Murrell, Anuroop Sriram, et al.. (2020). Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. Magnetic Resonance in Medicine. 84(6). 3054–3070. 128 indexed citations
8.
Defazio, Aaron. (2016). A Simple Practical Accelerated Method for Finite Sums. arXiv (Cornell University). 29. 676–684. 12 indexed citations
9.
Schmidt, Mark, et al.. (2015). Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields. ANU Open Research (Australian National University). 819–828. 6 indexed citations
10.
Defazio, Aaron & Thore Graepel. (2014). A Comparison of learning algorithms on the Arcade Learning Environment.. arXiv (Cornell University). 1 indexed citations
11.
Defazio, Aaron & Tibério S. Caetano. (2014). A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation. arXiv (Cornell University). 25. 1250–1258. 9 indexed citations
12.
Defazio, Aaron, et al.. (2012). A Graphical Model Formulation of Collaborative Filtering Neighbourhood Methods with Fast Maximum Entropy Training. arXiv (Cornell University). 555–562. 7 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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