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DE-GAN is proposed, a contrast-enhancing conditional GAN that combines input-adaptive dynamic convolutions, style-aware feature mixing, and coordinate encoding to synthesize slice-adaptive FLAIR images to synthesize slice-adaptive FLAIR images.
Conventional benchmarks miss critical structural failures in quantum circuit design, but HamQASBench exposes hidden pitfalls that could derail QAS efforts.
Achieving chemical accuracy with a search-free ansatz, this method outperforms traditional quantum architecture searches in estimating molecular ground-state energies.
