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Showing 8 open source projects for "pde"
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Speedy Claims became the top CMS-1500 Software by providing the best customer service imaginable to our thousands of clients all over America. Medical billing isn't the kind of thing most people get excited about - it is just a tedious task you have to do. But while it will never be a fun task, it doesn't have to be as difficult or time consumimg as it is now. With Speedy Claims CMS-1500 software you can get the job done quickly and easily, allowing you to focus on the things you love about your job, like helping patients. With a simple interface, powerful features to eliminate repetitive work, and unrivaled customer support, it's simply the best HCFA 1500 software available on the market. A powerful built-in error checking helps ensure your HCFA 1500 form is complete and correctly filled out, preventing CMS-1500 claims from being denied.
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BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function... -
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JUDI.jl
Julia Devito inversion
JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling... -
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MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
MethodOfLines.jl is a Julia package for automated finite difference discretization of symbolically defined PDEs in N dimensions. It uses symbolic expressions for systems of partial differential equations as defined with ModelingToolkit.jl, and Interval from DomainSets.jl to define the space(time) over which the simulation runs. This project is under active development, therefore the interface is subject to change. The docs will be updated to reflect any changes, please check back for current... -
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Surrogates.jl
Surrogate modeling and optimization for scientific machine learning
A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations... -
Cut through the noise and end information overload with Guru, an all-in-one wiki, intranet, and knowledge base that serves as your company's single source of truth.
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can... -
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wxMorlet implements the new algorithm (see "Documentation") for the computation of the continuous wavelet transform with the Morlet wavelet. wxMorlet calculates it as a numerical solution of the proper PDE and represents the results in a graphical form
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An object-oriented partial differential equation (PDE) solver, written in Python, based on a standard finite volume approach and includes interface tracking algorithms. *WARNING* The project is no longer using Sourceforge to maintain its repository.
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