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UAL Research Online

Items where Subject is "Neural Computing"

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Jump to: 2013 | 2015 | 2016 | 2019 | 2020
Number of items at this level: 16.

2013

Grierson, Mick and Kiefer, Chris (2013) NoiseBear: A Wireless Malleable Instrument Designed In Participation with Disabled Children. In: New Interfaces For Musical Expression, 27 - 30 May 2013, Daejeon, South Korea.

Grierson, Mick and Kiefer, Chris (2013) NoiseBear: a wireless malleable multiparametric controller for use in assistive technology contents. In: Extended Abstracts on Human Factors in Computing Systems, 27 April - 2 May 2013, Paris.

2015

Jakubowski, Kelly and Halpern, Andrea and Grierson, Mick and Stewart, Lauren (2015) The effect of exercise-induced arousal on chosen tempi for familiar melodies. Psychonomic Bulletin and Review, 22 (2). pp. 559-565. ISSN 1069-9384

2016

Kirk, Pedro and Grierson, Mick and Bodak, Rebeka and Ward, Nick and Brander, Fran and Kelly, Kate and Newman, Nicholas and Stewart, Lauren (2016) Motivating Stroke Rehabilitation Through Music: A Feasibility Study Using Digital Musical Instruments in the Homes. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, San Jose, USA, pp. 1781-1785. ISBN 978-1-4503-3362-7

Akten, Memo and Grierson, Mick (2016) Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks. In: Constructive Machine Learning Workshop, 10 December 2016, Barcelona, Spain.

Akten, Memo and Grierson, Mick (2016) Real-time interactive sequence generation and control with Recurrent Neural Network ensembles. In: Recurrent Neural Networks Symposium, 8 December 2016, Barcelona Spain.

2019

Parke-Wolfe, Samuel Thompson and Scurto, Hugo and Fiebrink, Rebecca (2019) Sound Control: Supporting Custom Musical Interface Design for Children with Disabilities. In: New Interfaces for Musical Expression (NIME), 3-6 June 2019, Porto Alegre, Brazil.

McCallum, Louis and Fiebrink, Rebecca (2019) Supporting Feature Engineering in End-User Machine Learning. In: CHI 2019 Workshop on Emerging Perspectives in Human-Centered Machine Learning, 4 May 2019, Glasgow, Scotland.

Holland, Simon and Fiebrink, Rebecca (2019) Machine Learning, Music and Creativity: An Interview with Rebecca Fiebrink. In: New Directions in Music and Human-Computer Interac- tion. Springer, Cham, Switzerland, pp. 259-267. ISBN 9783319920696

Gonzalez Diaz, Carlos and Perry, Phoenix and Fiebrink, Rebecca (2019) Interactive Machine Learning for More Expressive Game Interactions. In: IEEE Conference on Games (GOG) 2019, 20-23 August 2019, London, UK.

Broad, Terence and Grierson, Mick (2019) Searching for an (un)stable equilibrium: experiments in training generative models without data. In: Machine Learning for Creativity and Design, December 14t 2019, NeurIPS 2019 Workshop, Vancouver, Canada.

2020

Vigliensoni, Gabriel and McCallum, Louis and Maestre, Esteban and Fiebrink, Rebecca (2020) Generation and visualization of rhythmic latent spaces. In: The 2020 Joint Conference on AI Music Creativity, 19-23 October 2020.

Plant, Nicola and Zbyszynski, Michael and Gonzalez Diaz, Carlos and Hilton, Clarice and Fiebrink, Rebecca and Gibson, Ruth and Gillies, Marco and Perry, Phoenix and Martelli, Bruno (2020) Programming by Moving: Interactive Machine Learning for Embodied Interaction Design. In: NordiCHI'20 Workshop on Programming for Working Bodies, 26 October 2020, Online.

Plant, Nicola and Gibson, Ruth and Gonzalez Diaz, Carlos and Martelli, Bruno and Zbyszynski, Michael and Fiebrink, Rebecca and Gillies, Marco and Hilton, Clarice and Perry, Phoenix (2020) Movement interaction design for immersive media using interactive machine learning. In: 7th International Conference on Movement and Computing (MOCO '20), 15-17 July 2020, Online.

McCallum, Louis and Fiebrink, Rebecca (2020) The challenge of feature engineering in programming for moving bodies. In: NordiCHI '20 Workshop on Programming for Moving Bodies, 26 October 2020, Online.

Hilton, Clarice and Gonzalez Diaz, Carlos and Gibson, Ruth and Perry, Phoenix and Fiebrink, Rebecca and Zbyszynski, Michael and Plant, Nicola and Martelli, Bruno and Gillies, Marco (2020) InteractML: Node Based Tool to Empower Artists and Dancers in using Interactive Machine Learning for Designing Movement Interaction. In: NordiCHI '20 The UX of Interactive Machine Learning, 25 October 2020, Online.

This list was generated on Sat Jun 12 19:39:14 2021 BST.