Results 31 to 40 of about 165,146 (318)

apotschka/markov-chain-scenario-trees: First release

, 2019
<p>This is the first release of Markov chain scenario trees.</p> <p>Contents:</p> <ul> <li>A polynomial-time algorithm to generate optimally pruned Markov chain scenario trees</li> <li>Functions for ...
Andreas Potschka, Andreas Potschka (7111493)   +1 more
core   +1 more source

Stress History Establishes a Transient Tolerant State That Shapes Antibiotic Survival Upon Resuscitation

Advanced Science, EarlyView.
High‐throughput single‐cell analysis of resuscitating bacteria reveals a starvation‐history‐dependent transiently tolerant subpopulation that survives β$\beta$‐lactam exposure by temporarily reducing growth. Distinct from classical persisters, these actively growing yet dynamically modulated cells dominate survival across clinically relevant antibiotic
Kieran Abbott, Georgeos Hardo, Ruizhe Li, Jack Bradley, Ashraf Zarkan, Somenath Bakshi   +5 more
wiley   +1 more source

Transformers of markov chains

Information and Control, 1976
We investigate the possibility of synthesizing stable probability distribution generators on the basis of a complete system of deterministic elements and generators of random signals described by nonhomogeneous Markov chains. It is shown that such generators can be obtained by constructing some finite Moore automata with special transition functions ...
openaire   +2 more sources

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

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

Lipocalin‐2 activates hepatic stellate cells and promotes nonalcoholic steatohepatitis in high‐fat diet–fed Ob/Ob mice

Hepatology, EarlyView., 2022
Graphical summary of obesity‐induced NASH progression by LCN2 targeted to HSC activation. Abstract Background and Aims In obesity and type 2 diabetes mellitus, leptin promotes insulin resistance and contributes to the progression of NASH via activation of hepatic stellate cells (HSCs).
Kyung Eun Kim, Jaewoong Lee, Hyun Joo Shin, Eun Ae Jeong, Hye Min Jang, Yu Jeong Ahn, Hyeong Seok An, Jong Youl Lee, Meong Cheol Shin, Soo Kyoung Kim, Won Gi Yoo, Won Ho Kim, Gu Seob Roh   +12 more
wiley   +1 more source

On the containment condition for adaptive Markov Chain Monte Carlo algorithms [PDF]

, 2009
This paper considers ergodicity properties of certain adaptive Markov chain Monte Carlo (MCMC) algorithms for multidimensional target distributions, in particular Adaptive Metropolis and Adaptive Metropolis-within-Gibbs.
Rosenthal, Jeffrey S. (Jeffrey Seth), Bai, Yan, Roberts, Gareth O.   +2 more
core  

Attainability for Markov and Semi-Markov Chains

Mathematics
When studying Markov chain models and semi-Markov chain models, it is useful to know which state vectors n, where each component ni represents the number of entities in the state Si, can be maintained or attained. This question leads to the definitions of maintainability and attainability for (time-homogeneous) Markov chain models.
Brecht Verbeken, Marie-Anne Guerry
openaire   +3 more sources

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source