- STEM
- Engineering
- Electrical Engineering
- Signal Processing
- Digital Signal Processing
- Audio Processing
- STEM
- Engineering
- Electrical Engineering
- Signal Processing
- Digital Signal Processing
- Audio Signal Processing
- Technology
- Artificial Intelligence
- Machine Learning
- Scientific Machine Learning
- Physics Informed Machine Learning
Pipeline for VA Modelling with Physics-Informed Machine Learning
ADC - Audio Developer Conference via YouTube
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Explore a cutting-edge approach to virtual analog modeling in this conference talk from the Audio Developer Conference. Delve into a pipeline that combines Wave Digital Filters with neural networks for circuit modeling. Learn how the Differentiable Wave Digital Filters library was utilized to train a real-time deployable model of a diode clipper circuit. Discover the advantages of this methodology, including higher accuracy and comparable computation time to traditional white-box models. Gain insights from Christopher Johann Clarke, a PhD candidate specializing in multiphysics and AI/machine learning, as he presents this innovative approach to audio circuit modeling.
Syllabus
SWAP - Pipeline for VA Modelling with Physics-Informed Machine Learning - Christopher Johann Clarke
Taught by
ADC - Audio Developer Conference