Jack Parker-Holder

475 total citations
11 papers, 78 citations indexed

About

Jack Parker-Holder is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computational Theory and Mathematics. According to data from OpenAlex, Jack Parker-Holder has authored 11 papers receiving a total of 78 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Management Science and Operations Research and 2 papers in Computational Theory and Mathematics. Recurrent topics in Jack Parker-Holder's work include Reinforcement Learning in Robotics (7 papers), Advanced Bandit Algorithms Research (3 papers) and Machine Learning and Algorithms (2 papers). Jack Parker-Holder is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Advanced Bandit Algorithms Research (3 papers) and Machine Learning and Algorithms (2 papers). Jack Parker-Holder collaborates with scholars based in United Kingdom, United States and Netherlands. Jack Parker-Holder's co-authors include Stephen Roberts, Yingjie Miao, Marius Lindauer, André Biedenkapp, Baohe Zhang, Aleksandra Faust, Xingyou Song, Vu Nguyen, Frank Hutter and Roberto Calandra and has published in prestigious journals such as Journal of Artificial Intelligence Research, Oxford University Research Archive (ORA) (University of Oxford) and arXiv (Cornell University).

In The Last Decade

Jack Parker-Holder

9 papers receiving 75 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jack Parker-Holder United Kingdom	4	60	16	10	7	7	11	78
Zhaohan Daniel Guo United States	4	75 1.3×	13 0.8×	12 1.2×	6 0.9×	7 1.0×	5	91
André Biedenkapp Germany	4	67 1.1×	24 1.5×	11 1.1×	6 0.9×	6 0.9×	7	90
Dawid Ewald Poland	5	47 0.8×	24 1.5×	6 0.6×	6 0.9×	8 1.1×	8	69
Hubert Zarzycki Poland	5	49 0.8×	28 1.8×	11 1.1×	4 0.6×	7 1.0×	8	75
Aurelia Guy United States	1	39 0.7×	14 0.9×	13 1.3×	5 0.7×	8 1.1×	2	58
Carlos Florensa United States	4	40 0.7×	7 0.4×	23 2.3×	5 0.7×	4 0.6×	5	68
Andy Shih United States	5	59 1.0×	14 0.9×	4 0.4×	6 0.9×	2 0.3×	9	125
Stefan Depeweg Germany	4	60 1.0×	5 0.3×	14 1.4×	3 0.4×	7 1.0×	7	84
Ashish Khetan United States	5	24 0.4×	11 0.7×	6 0.6×	4 0.6×	3 0.4×	10	56
Léonard Hussenot United States	4	40 0.7×	4 0.3×	10 1.0×	3 0.4×	5 0.7×	5	50

Countries citing papers authored by Jack Parker-Holder

Since Specialization

Citations

This map shows the geographic impact of Jack Parker-Holder'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 Jack Parker-Holder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Parker-Holder more than expected).

Fields of papers citing papers by Jack Parker-Holder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack Parker-Holder. 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 Jack Parker-Holder. The network helps show where Jack Parker-Holder may publish in the future.

Co-authorship network of co-authors of Jack Parker-Holder

This figure shows the co-authorship network connecting the top 25 collaborators of Jack Parker-Holder. A scholar is included among the top collaborators of Jack Parker-Holder 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 Jack Parker-Holder. Jack Parker-Holder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Foerster, Jakob, Eric Hambro, Minqi Jiang, et al.. (2024). Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. 69747–69786. 2 indexed citations

Parker-Holder, Jack, et al.. (2022). Lyapunov Exponents for Diversity in Differentiable Games. 842–852.

Parker-Holder, Jack, Xingyou Song, André Biedenkapp, et al.. (2022). Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. Journal of Artificial Intelligence Research. 74. 517–568. 48 indexed citations

Kessler, Samuel, Jack Parker-Holder, Philip Ball, Stefan Zohren, & Stephen Roberts. (2022). Same State, Different Task: Continual Reinforcement Learning without Interference. Proceedings of the AAAI Conference on Artificial Intelligence. 36(7). 7143–7151. 10 indexed citations

Ball, Philip, et al.. (2021). Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. Oxford University Research Archive (ORA) (University of Oxford). 619–629. 1 indexed citations

Parker-Holder, Jack, et al.. (2021). Deep Reinforcement Learning with Dynamic Optimism.. arXiv (Cornell University). 2 indexed citations

Samvelyan, Mikayel, Robert Kirk, Vitaly Kurin, et al.. (2021). MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. arXiv (Cornell University). 3 indexed citations

Ball, Philip, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromański, & Stephen Roberts. (2020). Ready Policy One: World Building Through Active Learning. International Conference on Machine Learning. 1. 591–601. 9 indexed citations

Parker-Holder, Jack, Aldo Pacchiano, Krzysztof Choromański, & Stephen Roberts. (2020). Effective Diversity in Population Based Reinforcement Learning. Neural Information Processing Systems. 33. 18050–18062. 2 indexed citations

10.

Choromański, Krzysztof, Aldo Pacchiano, Jack Parker-Holder, et al.. (2019). When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies. arXiv (Cornell University). 1 indexed citations

11.

Choromański, Krzysztof, Aldo Pacchiano, Jack Parker-Holder, & Yunhao Tang. (2019). Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces..

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.

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