Twincher learns bijective representations of observations aligned with continuous system parameters to enable robust iterative inversion, showing better data efficiency and noise tolerance than standard inverse modeling on synthetic systems.
Invmap and witness simplicial variational auto-encoders.Machine Learning and Knowledge Extraction, 5(1):199–236, February 2023
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Twincher: Bijective Representation Learning for Robust Inversion of Continuous Systems
Twincher learns bijective representations of observations aligned with continuous system parameters to enable robust iterative inversion, showing better data efficiency and noise tolerance than standard inverse modeling on synthetic systems.