SVAR-FM uses simulator clamping to produce interventional distributions and flow matching to identify time series causal structures, with an error bound that predicts sign reversal of causal effects below a simulator accuracy threshold.
Tancogne-Dejean , author M
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Polarization-resolved high-harmonic generation spectra in bilayer Td-WTe2 exhibit robust signatures of mirror-symmetry breaking from sliding ferroelectricity, enabling all-optical identification of the polarization state.
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Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions
SVAR-FM uses simulator clamping to produce interventional distributions and flow matching to identify time series causal structures, with an error bound that predicts sign reversal of causal effects below a simulator accuracy threshold.
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Probing sliding ferroelectricity in bilayer T$_\mathrm{d}$-WTe$_2$ with high-harmonic generation
Polarization-resolved high-harmonic generation spectra in bilayer Td-WTe2 exhibit robust signatures of mirror-symmetry breaking from sliding ferroelectricity, enabling all-optical identification of the polarization state.