Author

Adam Watts

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#machine learning Preprint Oct 2026

Inverse Synthesis of Shock Time Series from Shock Response Spectra Using Ensembles of Conditional Variational Autoencoders

An earlier conditional variational autoencoder framework is extended with a recurrent decoder that predicts multiscale wavelet coefficients and reconstructs waveforms through an inverse discrete wavelet transform and demonstrates superior performance across four holdout benchmark datasets and competitive performance on...

Adam Watts, Charles Young, Ryan Bowering et al. · 0 citations

#machine learning Mar 2026

Inverse Reconstruction of Shock Time Series from Shock Response Spectrum Curves using Machine Learning

A conditional variational autoencoder (CVAE) that learns a data-driven inverse mapping from SRS to acceleration time series, establishing deep generative modeling as a scalable and efficient approach for inverse SRS reconstruction.

Adam Watts, Andrew Jeon, Destry A. Newton et al. · arXiv.org · 0 citations

#artificial intelligence Preprint Mar 2026

Toward Generalizable Deep Learning Based Peatland Fire Detection via Walsh Hadamard Transform and Domain Adaptation

An efficient deep learning framework for peatland fire detection based on a Walsh--Hadamard Transform enhanced ResNet-50 (WHT-ResNet-50), which improves feature representation while reducing model complexity and reduces inference cost while preserving detection accuracy is proposed.

Emadeldeen Hamdan, A. F. Tharima, Mohd Zahirasri Mohd Tohir et al. · 0 citations