Topic: pde Goto Github
Some thing interesting about pde
Some thing interesting about pde
pde,Generalized and Personalized
User: alexis12119
pde,Castro (Compressible Astrophysics): An adaptive mesh, astrophysical compressible (radiation-, magneto-) hydrodynamics simulation code for massively parallel CPU and GPU architectures.
Organization: amrex-astro
Home Page: http://amrex-astro.github.io/Castro
pde,An adaptive mesh hydrodynamics simulation code for low Mach number reacting flows
Organization: amrex-combustion
Home Page: https://amrex-combustion.github.io/PeleLM/
pde,A Julia package to perform Bifurcation Analysis
Organization: bifurcationkit
Home Page: https://bifurcationkit.github.io/BifurcationKitDocs.jl/stable
pde,This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
User: bogdanraonic3
Home Page: https://arxiv.org/abs/2302.01178
pde,BOUT++: Plasma fluid finite-difference simulation code in curvilinear coordinate systems
Organization: boutproject
Home Page: http://boutproject.github.io/
pde,Meshless large eddy simulation through the reformulated vortex particle method
Organization: byuflowlab
pde,Source code for APDE: Create and run Processing sketches on an Android device.
User: calsign
pde,PyClaw is a Python-based interface to the algorithms of Clawpack and SharpClaw. It also contains the PetClaw package, which adds parallelism through PETSc.
Organization: clawpack
Home Page: http://www.clawpack.com/pyclaw
pde,TCAD Semiconductor Device Simulator
Organization: devsim
Home Page: https://devsim.org
pde,Deep learning library for solving differential equations on top of PyTorch.
User: edgellm
pde,ETH course - Solving PDEs in parallel on GPUs
Organization: eth-vaw-glaciology
Home Page: https://pde-on-gpu.vaw.ethz.ch
pde,Encoding physics to learn reaction-diffusion processes
User: isds-neu
pde,Taylor-mode automatic differentiation for higher-order derivatives
Organization: juliadiff
Home Page: https://juliadiff.org/TaylorDiff.jl/
pde,Collection of resources about partial differential equations, graph neural networks, deep learning and dynamical system simulation
Organization: kaist-silab
pde,Simple finite element assemblers
User: kinnala
Home Page: https://scikit-fem.readthedocs.io
pde,A library for scientific machine learning and physics-informed learning
User: lululxvi
Home Page: https://deepxde.readthedocs.io
pde,Python package for numerical derivatives and partial differential equations in any number of dimensions.
User: maroba
pde,Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks" at ICLR 2022
User: martenlienen
Home Page: https://www.daml.in.tum.de/finite-element-networks
pde,Physics-Informed Neural networks for Advanced modeling
Organization: mathlab
Home Page: https://mathlab.github.io/PINA/
pde,Solve non-linear HJB equations.
User: matthieugomez
pde,🗿 dotfilery, configuration, environment settings, automation, etc. 🛖
User: megalithic
Home Page: https://megalithic.io
pde,Finite volume discretization tools for Python.
Organization: meshpro
pde,a collection of small and standalone utilities for image processing, written in C
User: mnhrdt
Home Page: https://git.sr.ht/~coco/imscript
pde,Learning in infinite dimension with neural operators.
Organization: neuraloperator
Home Page: https://neuraloperator.github.io/neuraloperator/dev/index.html
pde,This repository containts materials for End-to-End AI for Science
Organization: openhackathons-org
pde,FEATool - "Physics Simulation Made Easy" (Fully Integrated FEA, FEniCS, OpenFOAM, SU2 Solver GUI & Multi-Physics Simulation Platform)
User: precise-simulation
Home Page: https://www.featool.com
pde,R Language Mode in Processing for Creative Coding, created by @gaocegege, maintained by @jeremydouglass
Organization: processing-r
Home Page: https://processing-r.github.io/
pde,Source code for the Processing Core and Development Environment (PDE)
Organization: processing
Home Page: http://processing.org
pde,A library for dimensionality reduction on spatial-temporal PDE
User: pswpswpsw
Home Page: https://pswpswpsw.github.io/nif
pde,Simple one-dimensional examples of various hydrodynamics techniques
Organization: python-hydro
pde,A framework for hydrodynamics explorations and prototyping
Organization: python-hydro
Home Page: https://python-hydro.github.io/pyro2
pde,Solve Fractional Differential Equations using high performance numerical methods
Organization: scifracx
Home Page: https://scifracx.github.io/FractionalDiffEq.jl/dev/
pde,The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Organization: sciml
pde,Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqOperators/stable/
pde,Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqDocs/stable/
pde,A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
Organization: sciml
Home Page: https://docs.sciml.ai/FEniCS/stable/
pde,A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality
Organization: sciml
Home Page: https://docs.sciml.ai/HighDimPDE/stable/
pde,Automatic Finite Difference PDE solving with Julia SciML
Organization: sciml
Home Page: https://docs.sciml.ai/MethodOfLines/stable/
pde,An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Organization: sciml
Home Page: https://mtk.sciml.ai/dev/
pde,DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
Organization: sciml
Home Page: https://docs.sciml.ai/NeuralOperators/stable/
pde,Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
Organization: sciml
Home Page: https://docs.sciml.ai/NeuralPDE/stable/
pde,Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLBenchmarksOutput/stable/
pde,Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Organization: sciml
Home Page: https://tutorials.sciml.ai
pde,SG⁺⁺ – the numerical library for Sparse Grids in all their variants.
Organization: sgpp
Home Page: https://sgpp.sparsegrids.org
pde,A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
Organization: ucl-bug
pde,Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.
User: vavrines
Home Page: https://xiaotianbai.com/Kinetic.jl/dev
pde,Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
Organization: willcox-research-group
Home Page: https://willcox-research-group.github.io/rom-operator-inference-Python3
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