Lectures, Presentations & Media
Public discourse on algorithmic sound, neural synthesis, and constructive design.
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Filtered by: Machine-Learning
Learning Normal Patterns in Musical Loops
An unsupervised framework for analyzing audio patterns in musical loops through anomaly detection. Combines HTS-AT feature extraction with Deep SVDD to learn normal patterns without labeled training data, addressing variable-length audio challenges.
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Two complementary Python repositories for training and analyzing Growing Hierarchical Self-Organizing Maps, focusing on design decisions, trade-offs, and practical research workflows.
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An Interreg-funded collaboration applying advanced predictive modeling techniques to real-world energy management challenges in Arctic environments, integrating electric mobility with smart home technology.
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