Gavin Taylor
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
- Domain Adaptation and Few-Shot Learning
- Advanced Graph Neural Networks
- Neural Networks and Applications
- Stochastic Gradient Optimization Techniques
Papers in
-
- Adversarial Robustness in Machine Learning 4
- Reinforcement Learning in Robotics 3
- Neural Networks and Applications 2
- Stochastic Gradient Optimization Techniques 2
- Machine Learning and ELM 2
- Evolutionary Algorithms and Applications 1
-
- Advanced Multi-Objective Optimization Algorithms 2
- Co-authors
- Tom Goldstein (7 shared papers)Ronald Parr (3 shared papers)Zheng Xu (3 shared papers)Christoph Studer (2 shared papers)Hao Li (2 shared papers)Michael L. Littman (1 shared paper)Lihong Li (1 shared paper)Bharat Singh (1 shared paper)
- Journals
- Future Generation Computer Systems (1 paper)Systems Engineering (1 paper)Sensors (1 paper)Cryptologia (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- United StatesNorwaySaudi Arabia
In The Last Decade
Gavin Taylor
16 papers receiving 556 citations
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 356
- Computational Mathematics 4
- Computer Vision and Pattern Recognition 137
- Computational Theory and Mathematics 67
- Management Science and Operations Research 46
Countries citing papers authored by Gavin Taylor
This map shows the geographic impact of Gavin Taylor'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 Gavin Taylor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin Taylor more than expected).
Fields of papers citing papers by Gavin Taylor
This network shows the impact of papers produced by Gavin Taylor. 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 Gavin Taylor. The network helps show where Gavin Taylor may publish in the future.
Co-authors
The 25 scholars most cited alongside Gavin Taylor, 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 | 167 | |
| 2 | Neural Networks and Their Applications | 1996 | 76 |
| 3 | 2008 | 74 | |
| 4 | 2016 | 56 | |
| 5 | 2009 | 55 | |
| 6 | 2022 | 50 | |
| 7 | LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition | 2021 | 38 |
| 8 | 2010 | 28 | |
| 9 | 2021 | 11 | |
| 10 | Adaptive Consensus ADMM for Distributed Optimization | 2017 | 8 |
| 11 | 2019 | 8 | |
| 12 | 2016 | 7 | |
| 13 | 2023 | 5 | |
| 14 | 2019 | 5 | |
| 15 | MetaPoison: Practical General-purpose Clean-label Data Poisoning | 2020 | 3 |
| 16 | Introduction to the Symposium on AI and the Mitigation of Human Error | 2016 | 1 |
| 17 | 2018 | 1 | |
| 18 | Exploration Strategy Workshop | 2006 | 1 |
| 19 | 2024 | 0 |
About Gavin Taylor
Gavin Taylor is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Statistical and Nonlinear Physics, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 19 papers that have together received 594 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Reinforcement Learning in Robotics (3 papers), Neural Networks and Applications (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Machine Learning and ELM (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), COVID-19 diagnosis using AI (1 paper) and Evolutionary Algorithms and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (356 citations), Computational Mathematics (4 citations), Computer Vision and Pattern Recognition (137 citations), Computational Theory and Mathematics (67 citations) and Management Science and Operations Research (46 citations). Gavin Taylor has collaborated with scholars based in United States, Norway and Saudi Arabia. Frequent co-authors include Tom Goldstein, Ronald Parr, Zheng Xu, Christoph Studer, Hao Li, Michael L. Littman, Lihong Li, Bharat Singh, Ankit Patel and Chen Zhu. Their work appears in journals such as Future Generation Computer Systems, Systems Engineering, Sensors, Cryptologia and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.