31 citations · 69 across the 9 of their papers we have counts for
9 papers
Additive Multi-Step Markov Chains and the Curse of Dimensionality in Large Language Models
O. V. Usatenko, S. S. Melnyk, G. M. Pritula
Large-scale language models (LLMs) operate in extremely high-dimensional state spaces, where both token embeddings and their hidden representations create complex dependencies that…
Random telegraph processes with non-local memory
S. S. Apostolov, O. V. Usatenko, V. A. Yampol'skii +3
We study two-state (dichotomous, telegraph) random ergodic continuous-time processes with dynamics depending on their past. We take into account the history of process in an explic…
Information entropy and temperature of the binary Markov chains
O. V. Usatenko, S. S. Melnyk, G. M. Pritula +1
We propose two different approaches for introducing the information temperature of the binary N-th order Markov chains. The first approach is based on comparing the Markov sequence…
Memory-dependent noise-induced resonance and diffusion in non-markovian systems
S. S. Melnyk, O. V. Usatenko, V. A. Yampol'skii
We study the random processes with non-local memory and obtain new solutions of the Mori-Zwanzig equation describing non-markovian systems. We analyze the system dynamics depending…
Continuous stochastic processes with non-local memory
S. S. Melnyk, V. A. Yampol'skii, O. V. Usatenko
We study the non-Markovian random continuous processes described by the Mori-Zwanzig equation. As a starting point, we use the Markovian Gaussian Ornstein-Uhlenbeck process and int…
Signum Function Method for Generation of Correlated Dichotomic Chains
S. S. Apostolov, F. M. Izrailev, N. M. Makarov +3
We analyze the signum-generation method for creating random dichotomic sequences with prescribed correlation properties. The method is based on a binary mapping of the convolution…