energy-based models 1image classification 1random bond ising model 1sparse graphs 1spectral embedding 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification
V. S. Usatyuk, D. A. Sapozhnikov, S. I. Egorov
The paper proposes Kohn‑Sham Spectral Embedding (KSSE), a physics‑inspired, sparse‑graph spectral method that replaces dense CNN classifiers with a regularized Laplacian evaluated…
cs.LG2026
Natural Image Classification via Quasi-Cyclic Graph Ensembles and Random-Bond Ising Models at the Nishimori Temperature
V. S. Usatyuk, D. A. Sapozhnikov, S. I. Egorov
Modern multi-class image classification uses high-dimensional CNN features that incur large memory and computational costs and obscure the data manifold's geometry. Existing graph-…
cs.CV2025
Synthetic Image Detection via Spectral Gaps of QC-RBIM Nishimori Bethe-Hessian Operators
V. S. Usatyuk, D. A. Sapozhnikov, S. I. Egorov
The rapid advance of deep generative models such as GANs and diffusion networks now produces images that are virtually indistinguishable from genuine photographs, undermining media…