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arXiv · 2507.02109

Parametric Neural Amp Modeling with Active Learning

Florian Grötschla·Luca A. Lanzendörfer·Longxiang Jiao·Roger Wattenhofer
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Abstract

We introduce PANAMA, an active learning framework for the training of end-to-end parametric guitar amp models using a WaveNet-like architecture. With \model, one can create a virtual amp by recording samples that are determined by an active learning strategy to use a minimum amount of datapoints (i.e., amp knob settings). We show that gradient-based optimization algorithms can be used to determine the optimal datapoints to sample, and that the approach helps under a constrained number of samples.

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Florian Grötschla, Luca A. Lanzendörfer, Longxiang Jiao, Roger Wattenhofer. 2025-07-02. Parametric Neural Amp Modeling with Active Learning. https://arxiv.org/abs/2507.02109

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