Farzan Farnia
- Artificial Intelligence
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Statistical and Nonlinear Physics
- Co-authors
- David TseAyfer ÖzgürAsuman OzdaglarAli JadbabaieAmirhossein ReisizadehRamtin PedarsaniSoheil FeiziBei Yu
- Topics
- Adversarial Robustness in Machine Learning (3 papers)Gaussian Processes and Bayesian Inference (3 papers)Neural Networks and Applications (3 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionElectrical and Electronic Engineering
- Journals
- IEEE Journal on Selected Areas in CommunicationsarXiv (Cornell University)eScholarship (California Digital Library)
- Partner nations
- United StatesHong KongIran
In The Last Decade
Farzan Farnia
16 papers receiving 157 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 77
- Electrical and Electronic Engineering 67
- Computer Vision and Pattern Recognition 40
- Computer Networks and Communications 20
- Statistical and Nonlinear Physics 10
Countries citing papers authored by Farzan Farnia
This map shows the geographic impact of Farzan Farnia'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 Farzan Farnia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Farzan Farnia more than expected).
Fields of papers citing papers by Farzan Farnia
This network shows the impact of papers produced by Farzan Farnia. 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 Farzan Farnia. The network helps show where Farzan Farnia may publish in the future.
Co-authorship network of co-authors of Farzan Farnia
This figure shows the co-authorship network connecting the top 25 collaborators of Farzan Farnia. A scholar is included among the top collaborators of Farzan Farnia 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 Farzan Farnia. Farzan Farnia 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 | 3 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 6 | |
| 6 | 0 | |
| 7 | 7 | |
| 8 | 16 | |
| 9 | Do GANs always have Nash equilibria | 13 |
| 10 | Robust Federated Learning: The Case of Affine Distribution Shifts | 2 |
| 11 | 13 | |
| 12 | 3 | |
| 13 | A Convex Duality Framework for GANs | 11 |
| 14 | Generalizable Adversarial Training via Spectral Normalization. | 11 |
| 15 | A Spectral Approach to Generalization and Optimization in Neural Networks | 1 |
| 16 | A minimax approach to supervised learning | 17 |
| 17 | 53 | |
| 18 | 1 | |
| 19 | 2 |
About Farzan Farnia
Farzan Farnia is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 19 papers that have together received 162 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Gaussian Processes and Bayesian Inference (3 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (77 citations), Computer Vision and Pattern Recognition (40 citations) and Electrical and Electronic Engineering (67 citations). Farzan Farnia has collaborated with scholars based in United States, Hong Kong and Iran. Frequent co-authors include David Tse, Ayfer Özgür, Asuman Ozdaglar, Ali Jadbabaie, Amirhossein Reisizadeh, Ramtin Pedarsani, Soheil Feizi, Bei Yu, S. Jamaloddin Golestani and Subhro Das. Their work appears in journals such as IEEE Journal on Selected Areas in Communications, 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.