Results 41 to 50 of about 68,685,272 (228)

Probability measures on product spaces with uniform metrics [PDF]

, 2017
For a countable product of complete separable metric spaces with a topology induced by a uniform metric, the set of Borel probability measures coincides with the set of completions of probability measures on the product o-algebra.
Hellwig, M., Hellwig, Martin, Martin F. Hellwig   +2 more
core   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

PROJECTIVE SYSTEM APPROACH TO THE MARTINGALE CHARACTERIZATION OF THE ABSENCE OF ARBITRAGE [PDF]

The equivalence between the absence of arbitrage and the existence of an equivalent martingale measure fails when an infinite number of trading dates is considered. By enlarging the set of states of nature and the probability measure through a projective
María José Muñoz-Bouzo, Miguel Ángel Mirás, Alejandro Balbás   +2 more
core  

Some results for probability measures on linear topological vector spaces with an application to Strassen's log log law

Journal of Functional Analysis, 1973
AbstractWe prove some results regarding tight probability measures on real Frechet spaces and countable strict inductive limits of these spaces. These results are applied to Gaussian measures and to construct a Brownian motion on such spaces. We then prove the log log law of Strassen for this Brownian motion.
openaire   +2 more sources

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source

"Uniform Measures On Inverse Limit Spaces" [PDF]

Motivated by problems from dynamic economic models, we consider the problem of defining a uniform measure on inverse limit spaces. Let f be a function from a compact metric space X into itself where f is continuous, onto and piecewise one-to-one.
David R. Stockman
core  

Bi-topological spaces [PDF]

, 1971
Kelly initiated the study of bi-topological spaces in [3]. In this paper the concepts of pairwise-T, pairwise regular, pairwise Hausdorff, quasi-pseudo-metrizable, and quasi-metrizable are introduced, and the following theorem is proved. Theorem.
Garner, Betty Ruffin, NC DOCKS at The University of North Carolina at Greensboro   +1 more
core  

Topological semi-conjugacy between dynamical systems induced on the space of probability measures and subshifts of finite type, and chaos

Portugaliae Mathematica
This paper establishes topological semi-conjugacy between a symbolic dynamical system (\Sigma_{A},\sigma_{A}) and the system (M(X),T_{M}) induced on the space of ...
Hyon Hui Ju, Chol San Kim, Jin Hyon Kim
openaire   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source