3 citations · 4 across the 19 of their papers we have counts for
19 papers
Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification
V. S. Usatyuk, D. A. Sapozhnikov, S. I. Egorov
We propose Kohn-Sham Spectral Embedding (KSSE), an energy-based model replacing the top-layer classifier of convolutional networks with a sparse-graph spectral embedding at the Nis…
Diffusion-Guided Feature Selection via Nishimori Temperature: Noise-Based Spectral Embedding
Vasiliy S. Usatyuk, Denis A. Sapozhnikov, Sergey I. Egorov
We propose Noise-Based Spectral Embedding (NBSE), a physics-informed framework for selecting informative features from high-dimensional data without greedy search. NBSE constructs…
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…
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-…
Cyclic Group Projection for Enumerating Quasi-Cyclic Codes Trapping Sets
Vasiliy Usatyuk, Yury Kuznetsov, Sergey Egorov
This paper introduces a novel approach to enumerate and assess Trapping sets in quasi-cyclic codes, those with circulant sizes that are non-prime numbers. Leveraging the quasi-cycl…
Topology-Aware Exploration of Energy-Based Models Equilibrium: Toric QC-LDPC Codes and Hyperbolic MET QC-LDPC Codes
Vasiliy Usatyuk, Denis Sapozhnikov, Sergey Egorov
This paper presents a method for achieving equilibrium in the ISING Hamiltonian when confronted with unevenly distributed charges on an irregular grid. Employing (Multi-Edge) QC-LD…