Amir Gholami
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Signal Processing top 10%
- Topics
- Advanced Neural Network Applications (13 papers)Stochastic Gradient Optimization Techniques (5 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Journals
- Journal of Mathematical BiologyarXiv (Cornell University)eScholarship (California Digital Library)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Amir Gholami
22 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 657
- Computer Vision and Pattern Recognition 591
- Electrical and Electronic Engineering 156
- Computer Networks and Communications 53
- Signal Processing 48
Countries citing papers authored by Amir Gholami
This map shows the geographic impact of Amir Gholami'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 Amir Gholami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amir Gholami more than expected).
Fields of papers citing papers by Amir Gholami
This network shows the impact of papers produced by Amir Gholami. 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 Amir Gholami. The network helps show where Amir Gholami may publish in the future.
Co-authorship network of co-authors of Amir Gholami
This figure shows the co-authorship network connecting the top 25 collaborators of Amir Gholami. A scholar is included among the top collaborators of Amir Gholami 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 Amir Gholami. Amir Gholami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 8 | |
| 6 | 49 | |
| 7 | 22 | |
| 8 | 88 | |
| 9 | 195 | |
| 10 | 65 | |
| 11 | 8 | |
| 12 | Q-BERT: Hessian Based Ultra Low Precision Quantization of BERTbreakdown → | 223 |
| 13 | 28 | |
| 14 | 224 | |
| 15 | Hessian-based Analysis of Large Batch Training and Robustness to Adversaries | 8 |
| 16 | 40 | |
| 17 | 18 | |
| 18 | 6 | |
| 19 | Integrated Model and Data Parallelism in Training Neural Networks. | 3 |
| 20 | FFT, FMM, or MULTIGRID? A comparative study of state-of-the-art poisson solvers. | 2 |
About Amir Gholami
Amir Gholami is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Hardware and Architecture, having authored 23 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (13 papers), Stochastic Gradient Optimization Techniques (5 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (591 citations), Artificial Intelligence (657 citations) and Computational Mathematics (11 citations). Amir Gholami has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Kurt Keutzer, Michael W. Mahoney, Zhewei Yao, Zhen Dong, Sheng Shen, Yaohui Cai, Jiayu Ye, Linjian Ma, Zhen Dong and Mustafa Mustafa. Their work appears in journals such as Journal of Mathematical Biology, arXiv (Cornell University) and eScholarship (California Digital Library).
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.