GQKAE uses quantum-inspired Kolmogorov-Arnold networks to reduce parameters by 66% in generative quantum eigensolvers while achieving chemical accuracy on H4, N2, LiH, and other molecules.
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Denoising particle filters train state estimators on individual transitions via score matching, then use the learned denoiser with a dynamics model to approximate Bayesian filtering step-by-step, matching end-to-end baselines while preserving composability.
Agentic AI enables coverless semantic steganography without private keys or cover images, delivering higher capacity and security than prior schemes in semantic communication.
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Generative Quantum-inspired Kolmogorov-Arnold Eigensolver
GQKAE uses quantum-inspired Kolmogorov-Arnold networks to reduce parameters by 66% in generative quantum eigensolvers while achieving chemical accuracy on H4, N2, LiH, and other molecules.
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Denoising Particle Filters: Learning State Estimation with Single-Step Objectives
Denoising particle filters train state estimators on individual transitions via score matching, then use the learned denoiser with a dynamics model to approximate Bayesian filtering step-by-step, matching end-to-end baselines while preserving composability.
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Secure Intellicise Wireless Network: Agentic AI for Coverless Semantic Steganography Communication
Agentic AI enables coverless semantic steganography without private keys or cover images, delivering higher capacity and security than prior schemes in semantic communication.