Results 51 to 60 of about 1,572 (217)

On Learning Markov Chains

CoRR, 2018
The problem of estimating an unknown discrete distribution from its samples is a fundamental tenet of statistical learning. Over the past decade, it attracted significant research effort and has been solved for a variety of divergence measures. Surprisingly, an equally important problem, estimating an unknown Markov chain from its samples, is still far
Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati   +2 more
openaire   +3 more sources

PDIA6–SCD1 Axis Rewires Lipid Metabolism to Drive Gastric Cancer Progression

Advanced Science, EarlyView.
Protein disulfide isomerase A6 (PDIA6) is identified as an oncogenic driver in gastric cancer. PDIA6 directly binds and stabilizes SCD1 by limiting its ubiquitin–proteasome‐mediated degradation, thereby sustaining monounsaturated fatty acid (MUFA)‐enriched lipid homeostasis and lipid metabolic reprogramming.
Zhen Tian, Yifan Cheng, Jiajie Zhou, Ruiqi Li, Shuai Zhao, Ben Li, Zijie Xu, Mengli Zi, Yayan Fu, Chenkai Zhang, Qiannan Sun, Shantanu Baral, Sen Wang, Daorong Wang   +13 more
wiley   +1 more source

Subgeometric Ergodicity under Random-Time State-Dependent Drift Conditions

Journal of Probability and Statistics, 2014
Motivated by possible applications of Lyapunov techniques in the stability of stochastic networks, subgeometric ergodicity of Markov chains is investigated.
Mokaedi V. Lekgari
doaj   +1 more source

Learning Moisture‐Induced Damage From Vision: Diffusion Models for Real‐Time Monitoring of Additive Manufacturing Processes

Advanced Science, EarlyView.
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung, Yuna Yoo, Dharneedar Ravichandran, Dahyun Daniel Lim, Grace X. Gu   +4 more
wiley   +1 more source

Quantum speedup for nonreversible Markov chains

Nature Communications
Quantum algorithms can potentially solve a handful of problems more efficiently than their classical counterparts. In that context, it has been discussed that Markov chains problems could be solved significantly faster using quantum computing.
Baptiste Claudon, Jean-Philip Piquemal, Pierre Monmarché   +2 more
doaj   +1 more source

Forecasting land use and land cover change as a tool for optimising adaptation to climate change: Examples of selected Second-Tier Cities of the V4 Group

Bulletin of Geography. Socio-Economic Series
Second-tier cities are an important element in the socio-economic development of each country, including V4 countries. The result is a dynamic change in land use/cover patterns.
Marcin Feltynowski, Agnieszka Rzeńca, Agnieszka Palma   +2 more
doaj   +1 more source

Subgeometric Ergodicity Analysis of Continuous-Time Markov Chains under Random-Time State-Dependent Lyapunov Drift Conditions

Journal of Probability and Statistics, 2014
We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs). We are mainly concerned with making use of the available results on deterministic state-dependent drift ...
Mokaedi V. Lekgari
doaj   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

PageRank of Gluing Networks and Corresponding Markov Chains

Mathematics
This paper studies Google’s PageRank algorithm. By an innovative application of the method of gluing Markov chains, we study the properties of Markov chains and extend their applicability by accounting for the damping factor and the personalization ...
Xuqian Ben Han, Shihao Wang, Chenglong Yu   +2 more
doaj   +1 more source

On automorphisms of Markov chains [PDF]

Transactions of the American Mathematical Society, 1992
We prove several theorems about automorphisms of Markov chains, using the weight-per-symbol polytope.
Krieger, Wolfgang, Marcus, Brian, Tuncel, Selim   +2 more
openaire   +1 more source