Bradly C. Stadie
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition
- Biomedical Engineering
- Computational Theory and Mathematics
- Co-authors
- Pieter AbbeelIlya SutskeverMarcin AndrychowiczYan DuanJonas SchneiderWojciech ZarembaHarris ChanJimmy Ba
- Topics
- Reinforcement Learning in Robotics (5 papers)Domain Adaptation and Few-Shot Learning (3 papers)Metaheuristic Optimization Algorithms Research (2 papers)
- Cited by
- Artificial IntelligenceControl and Systems EngineeringComputer Vision and Pattern Recognition
- Journals
- npj Digital MedicinearXiv (Cornell University)Neural Information Processing Systems
- Partner nations
- United StatesCanadaPoland
In The Last Decade
Bradly C. Stadie
9 papers receiving 166 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 124
- Control and Systems Engineering 65
- Computer Vision and Pattern Recognition 57
- Biomedical Engineering 13
- Computational Theory and Mathematics 9
Countries citing papers authored by Bradly C. Stadie
This map shows the geographic impact of Bradly C. Stadie'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 Bradly C. Stadie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bradly C. Stadie more than expected).
Fields of papers citing papers by Bradly C. Stadie
This network shows the impact of papers produced by Bradly C. Stadie. 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 Bradly C. Stadie. The network helps show where Bradly C. Stadie may publish in the future.
Co-authorship network of co-authors of Bradly C. Stadie
This figure shows the co-authorship network connecting the top 25 collaborators of Bradly C. Stadie. A scholar is included among the top collaborators of Bradly C. Stadie 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 Bradly C. Stadie. Bradly C. Stadie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | Learning Intrinsic Rewards as a Bi-Level Optimization Problem | 2 |
| 5 | 18 | |
| 6 | Evolved Policy Gradients | 16 |
| 7 | The Importance of Sampling inMeta-Reinforcement Learning | 3 |
| 8 | One-Shot Imitation Learning | 116 |
| 9 | Third-Person Imitation Learning | 12 |
About Bradly C. Stadie
Bradly C. Stadie is a scholar working on Health Informatics, Artificial Intelligence and Computational Theory and Mathematics, having authored 9 papers that have together received 177 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Metaheuristic Optimization Algorithms Research (2 papers). The work is most often cited by research in Artificial Intelligence (124 citations), Control and Systems Engineering (65 citations) and Computer Vision and Pattern Recognition (57 citations). Bradly C. Stadie has collaborated with scholars based in United States, Canada and Poland. Frequent co-authors include Pieter Abbeel, Ilya Sutskever, Marcin Andrychowicz, Yan Duan, Jonas Schneider, Wojciech Zaremba, Harris Chan, Jimmy Ba, Rein Houthooft and Jonathan Ho. Their work appears in journals such as npj Digital Medicine, arXiv (Cornell University) and Neural Information Processing Systems.
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.