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Chaitra Agrahar

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Open access Aug 2026

Deep learning of dynamic signatures resolves mechanistic ambiguity in complex signaling networks

An AI-driven framework treating model dynamics as learnable signatures is introduced, using deep learning autoencoders to embed the dynamic signatures of thousands of competing models into a low-dimensional latent space and provides a rigorous, full-state alternative to scalar metrics.

Mustafa Ozen, Chaitra Agrahar, Francesca Zappa et al. · 0 citations

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