Josue Ortega
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Visual perception and processing mechanisms
- Face Recognition and Perception
- Memory and Neural Mechanisms
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- Cell Image Analysis Techniques
Papers in
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- Adversarial Robustness in Machine Learning 1
- Neural Networks and Applications 1
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- Model Reduction and Neural Networks 2
- Co-authors
- David Cox (1 shared paper)Charlotte Moerman (1 shared paper)Martin Schrimpf (1 shared paper)Gabriel Kreiman (1 shared paper)William Lotter (1 shared paper)Hanlin Tang (1 shared paper)Ana Paredes (1 shared paper)Fabio Anselmi (2 shared papers)
- Journals
- Biological Psychiatry (1 paper)Proceedings of the National Academy of Sciences (1 paper)Nature Machine Intelligence (1 paper)PLoS Computational Biology (1 paper)Frontiers in Artificial Intelligence (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Josue Ortega
6 papers receiving 136 citations
Peers
Comparison fields: 5 of 49
- Cognitive Neuroscience 95
- Biophysics 10
- Computer Vision and Pattern Recognition 30
- Sensory Systems 6
- Artificial Intelligence 36
Countries citing papers authored by Josue Ortega
This map shows the geographic impact of Josue Ortega'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 Josue Ortega with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josue Ortega more than expected).
Fields of papers citing papers by Josue Ortega
This network shows the impact of papers produced by Josue Ortega. 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 Josue Ortega. The network helps show where Josue Ortega may publish in the future.
Co-authors
The 25 scholars most cited alongside Josue Ortega, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 110 | |
| 2 | 2023 | 13 | |
| 3 | 2024 | 7 | |
| 4 | 2022 | 5 | |
| 5 | A Functional Characterization of Randomly Initialized Gradient Descent in Deep ReLU Networks | 2019 | 2 |
| 6 | 2025 | 1 |
About Josue Ortega
Josue Ortega is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Cognitive Neuroscience, Computer Networks and Communications and Molecular Biology, having authored 6 papers that have together received 138 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (2 papers), Face Recognition and Perception (1 paper), Energy Efficient Wireless Sensor Networks (1 paper), Adversarial Robustness in Machine Learning (1 paper), Brain Tumor Detection and Classification (1 paper), Neural dynamics and brain function (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Cognitive Neuroscience (95 citations), Biophysics (10 citations), Computer Vision and Pattern Recognition (30 citations), Sensory Systems (6 citations) and Artificial Intelligence (36 citations). Josue Ortega has collaborated with scholars based in United States and Germany. Frequent co-authors include David Cox, Charlotte Moerman, Martin Schrimpf, Gabriel Kreiman, William Lotter, Hanlin Tang, Ana Paredes, Fabio Anselmi, Ankit Patel and Jessica A. Cardin. Their work appears in journals such as Biological Psychiatry, Proceedings of the National Academy of Sciences, Nature Machine Intelligence, PLoS Computational Biology and Frontiers in Artificial Intelligence.
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.