Recursive formalism computes scattering-order-resolved photon escape probabilities in slab Thomson media, yielding exact mean scattering numbers like ⟨N⟩=2τ and eigenmode limits for high orders, verified by Monte Carlo.
Cooley and John W
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WHET applies fine-grained coefficient-to-slot transforms, plaintext compression, and modulus raising plus lightweight hardware tweaks to FHE accelerators, delivering 1.38-8.74x per-area gains and sub-millisecond CKKS bootstrapping.
STAL transfers spectral tail uplift cues via a frequency teacher to train a spatial detector for AI-generated images, discarding frequency modules at inference for strong cross-generator generalization.
A temporal spectral noise-floor adaptation algorithm enables reliable event triggering in IoT mesh networks by suppressing nuisance triggers from environmental non-stationarity while preserving sensitivity to true signals.
citing papers explorer
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Photon Escape from Slab Thomson Media: A Scattering-order-resolved Recursive Formalism for Comptonization Applications
Recursive formalism computes scattering-order-resolved photon escape probabilities in slab Thomson media, yielding exact mean scattering numbers like ⟨N⟩=2τ and eigenmode limits for high orders, verified by Monte Carlo.
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WHET: Welding Homomorphic Encryption to Accelerator Architectures
WHET applies fine-grained coefficient-to-slot transforms, plaintext compression, and modulus raising plus lightweight hardware tweaks to FHE accelerators, delivering 1.38-8.74x per-area gains and sub-millisecond CKKS bootstrapping.
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Spectral Tail Auxiliary Learning for AI-Generated Image Detection
STAL transfers spectral tail uplift cues via a frequency teacher to train a spatial detector for AI-generated images, discarding frequency modules at inference for strong cross-generator generalization.
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Temporal Spectral Noise-Floor Adaptation for Error-Intolerant Trigger Integrity in IoT Mesh Networks
A temporal spectral noise-floor adaptation algorithm enables reliable event triggering in IoT mesh networks by suppressing nuisance triggers from environmental non-stationarity while preserving sensitivity to true signals.