Owen Lockwood
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics
- Atomic and Molecular Physics, and Optics
- Computer Networks and Communications
- Co-authors
- Mei SiPeter WeißGuillaume Verdon
- Topics
- Reinforcement Learning in Robotics (2 papers)Quantum Computing Algorithms and Architecture (2 papers)Data Stream Mining Techniques (2 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsElectrical and Electronic Engineering
- Journals
- Physical Review ResearcharXiv (Cornell University)Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
- Partner nations
- United StatesCanada
In The Last Decade
Owen Lockwood
5 papers receiving 123 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 99
- Electrical and Electronic Engineering 27
- Computational Theory and Mathematics 18
- Atomic and Molecular Physics, and Optics 14
- Computer Networks and Communications 8
Countries citing papers authored by Owen Lockwood
This map shows the geographic impact of Owen Lockwood'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 Owen Lockwood with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Owen Lockwood more than expected).
Fields of papers citing papers by Owen Lockwood
This network shows the impact of papers produced by Owen Lockwood. 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 Owen Lockwood. The network helps show where Owen Lockwood may publish in the future.
Co-authorship network of co-authors of Owen Lockwood
This figure shows the co-authorship network connecting the top 25 collaborators of Owen Lockwood. A scholar is included among the top collaborators of Owen Lockwood 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 Owen Lockwood. Owen Lockwood is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 4 | |
| 3 | 25 | |
| 4 | Replicating Softmax Deep Double Deterministic Policy Gradients | 1 |
| 5 | 86 |
About Owen Lockwood
Owen Lockwood is a scholar working on Artificial Intelligence, Statistics and Probability and Atomic and Molecular Physics, and Optics, having authored 5 papers that have together received 124 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (2 papers), Quantum Computing Algorithms and Architecture (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (99 citations), Computational Theory and Mathematics (18 citations) and Electrical and Electronic Engineering (27 citations). Owen Lockwood has collaborated with scholars based in United States and Canada. Frequent co-authors include Mei Si, Peter Weiß and Guillaume Verdon. Their work appears in journals such as Physical Review Research, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment.
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.