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Structured Unitary Tensor Network Representations for Circuit-Efficient Quantum Data Encoding
TNQE uses structured unitary tensor networks to learn shallow, resource-efficient quantum data encoding circuits that achieve 0.04x the depth of amplitude encoding and scale to high-resolution images on real hardware.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5