Ross Goroshin
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Human-Computer Interaction top 5%
- Aerospace Engineering
- Co-authors
- Yann LeCunJonathan TompsonChristoph BreglerArjun JainAndrea BaninoKoray KavukcuogluFabio ViolaDharshan Kumaran
- Topics
- Generative Adversarial Networks and Image Synthesis (3 papers)Image and Signal Denoising Methods (2 papers)Underwater Acoustics Research (2 papers)
- Journals
- arXiv (Cornell University)Neural Information Processing SystemsInternational Conference on Learning Representations
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Ross Goroshin
8 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Computer Vision and Pattern Recognition 664
- Artificial Intelligence 421
- Biomedical Engineering 100
- Human-Computer Interaction 91
- Aerospace Engineering 77
Countries citing papers authored by Ross Goroshin
This map shows the geographic impact of Ross Goroshin'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 Ross Goroshin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ross Goroshin more than expected).
Fields of papers citing papers by Ross Goroshin
This network shows the impact of papers produced by Ross Goroshin. 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 Ross Goroshin. The network helps show where Ross Goroshin may publish in the future.
Co-authorship network of co-authors of Ross Goroshin
This figure shows the co-authorship network connecting the top 25 collaborators of Ross Goroshin. A scholar is included among the top collaborators of Ross Goroshin 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 Ross Goroshin. Ross Goroshin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches | 2 |
| 2 | 173 | |
| 3 | Unsupervised Feature Learning from Temporal Data | 2 |
| 4 | Efficient object localization using Convolutional Networksbreakdown → | 805 |
| 5 | 62 | |
| 6 | 17 | |
| 7 | 7 | |
| 8 | 1 |
About Ross Goroshin
Ross Goroshin is a scholar working on Computer Vision and Pattern Recognition, Oceanography and Artificial Intelligence, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Image and Signal Denoising Methods (2 papers) and Underwater Acoustics Research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (664 citations), Human-Computer Interaction (91 citations) and Artificial Intelligence (421 citations). Ross Goroshin has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Yann LeCun, Jonathan Tompson, Christoph Bregler, Arjun Jain, Andrea Banino, Koray Kavukcuoglu, Fabio Viola, Dharshan Kumaran, Misha Denil and Hubert Soyer. Their work appears in journals such as arXiv (Cornell University), Neural Information Processing Systems and International Conference on Learning Representations.
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.