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Data Study Group team. (2022, January 5). Data Study Group Final Report: Entale. Zenodo. https://doi.org/10.5281/zenodo.5820436

Data Study Group team. (2022, January 4). Data Study Group Final Report: Entale. Zenodo. https://doi.org/10.5281/zenodo.5818331

Wright, J., Leslie, D., Raab, C, Kitagawa, F., Ostmann, F., and Briggs, M. (2021). Privacy, Agency and Trust in Human-AI Ecosystems: Interim Report. The Alan Turing Institute.

Ed Chalstrey, Research Data Scientist, Research Engineering Group, The Alan Turing Institute. October 2021.

Bing Zhai, Ignacio Perez-Pozuelo, Emma A.D. Clifton, Joao Palotti, and Yu Guan. 2020. Making Sense of Sleep: Multimodal Sleep Stage Classification in a Large, Diverse Population Using Movement and Cardiac Sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 2, Article 67 (June 2020), 33 pages. https://doi.org/10.1145/3397325

Mower, CE, Moura, J & Vijayakumar, S 2021, Skill-based Shared Control. in Robotics: Science and Systems 2021. Robotics: Science and Systems 2021, 12/07/21.

Wang, J, Kim, S, Vijayakumar, S & Tonneau, S 2021, Multi-Fidelity Receding Horizon Planning for Multi Contact Locomotion. in IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids 2020). 20th IEEE-RAS International Conference on Humanoid Robots, Munich, Bavaria, Germany, 19/07/21.

Data Study Group team. (2021, July 22). Reinforcement Learning Study Group Report – February 2021. Zenodo. https://doi.org/10.5281/zenodo.5121558

Chris J Dent, Michael Goldstein, Andrew Wright, Henry P. Wynn (2020, August 4). The use of multiple models within an organisation. https://arxiv.org/abs/2008.11813.

Song H., Flach P., Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing, International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 6, No. 5 (2021)

Data Study Group team. (2021, June 18). Data Study Group Final Report: The National Archives, UK. Zenodo. https://doi.org/10.5281/zenodo.4981184

Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks. Lim, D-Y. & Sabanis, S. 2021. arXiv:2105.13937 [cs.LG]