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(IN PROGRESS) Harley, N. & Wiggins, G. A. (2022). Abstract representation of musical knowledge for collab- orative scholarship.

(IN PROGRESS) Wiggins, G. A., Homer, S., Harley, N. & Loro Velardo, F. (2022). A new approach to oscillatory representations of percepts and sequential abstract predictive knowledge in music. Journal of Cognition.

Carnovalini, F., Harley, N., Homer, S. T., Rodà, A. & Wiggins, G. A. (2021). Meta-Evaluating Quantitative Internal Evaluation: A Practical Approach for Developers. In Proceedings of the 12th International Conference on Computational Creativity (ICCC ’21), (pp. 213-217).

Carnovalini, F., Rodà, A., Harley, N., Homer, S. T. & Wiggins, G. A. (2021). A new corpus for computational music research and a novel method for musical structure analysis. In Au- dio Mostly 2021 (AM ’21). Association for Computing Machinery, New York, NY, USA, (pp. 264–267).

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