Results 231 to 240 of about 175,748 (328)

On a stochastic fractional partial differential equation driven by a Lévy space-time white noise

, 2009
Kehua Shi, Yongjin Wang
openalex   +1 more source

AInsectID Version 1.1: An Insect Species Identification Software Based on the Transfer Learning of Deep Convolutional Neural Networks

Advanced Intelligent Discovery, EarlyView.
This paper describes the basis for AInsectID Version 1, a GUI‐operable open‐source insect species identification, color processing, and image analysis software. This paper discusses our methods of algorithmic development, coupled to rigorous machine training used to enable high levels of validation accuracy.
Haleema Sadia, Parvez Alam
wiley   +1 more source

Guided simulation of conditioned chemical reaction networks. [PDF]

Stat Inference Stoch Process
Corstanje M, Meulen FV.
europepmc   +1 more source

A unified controllability/observability theory for some stochastic and deterministic partial differential equations

, 2010
Xu Zhang
openalex   +2 more sources

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Simulating the non-Hermitian dynamics of financial option pricing with quantum computers. [PDF]

Sci Rep
Kumar S, Wilmott CM.
europepmc   +1 more source

The Itô integral for a certain class of Lévy processes and its application to stochastic partial differential equations

, 2010
Erika Hausenblas
openalex   +2 more sources

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Isotropic Q-fractional Brownian motion on the sphere: regularity and fast simulation. [PDF]

Philos Trans A Math Phys Eng Sci
Lang A, Müller B.
europepmc   +1 more source

Strong Solution of Backward Stochastic Partial Differential Equations in $C^2$ Domains

, 2010
Kai Du, Shanjian Tang
openalex   +2 more sources