Pinned Repositories
ModelingToolkitNeuralNets.jl
Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)
DS19Presentation
Materials for the SIAM DS19 Presentation
LaserTypes.jl
A common interface for different laser types
MasterThesis
My Master Thesis
Nuclear-surface-vibrations
Codes for articles analyzing the chaotic dynamics of nuclear surface vibrations
ParticleAccelerations.jl
PkgCite.jl
Cite Julia packages in your papers the easy way
SDFReader.jl
Read SDF files created by EPOCH
singularity-recipes
Singularity container recipes
StorageGraphs.jl
Store hierarchical data in graphs in a non-redundant way
SebastianM-C's Repositories
SebastianM-C/PkgCite.jl
Cite Julia packages in your papers the easy way
SebastianM-C/LaserTypes.jl
A common interface for different laser types
SebastianM-C/SDFReader.jl
Read SDF files created by EPOCH
SebastianM-C/Plasma.jl
An interface for accelerated simulation of high-dimensional collisionless and electrostatic plasmas.
SebastianM-C/SDFResults.jl
Read and analyze EPOCH simulation data
SebastianM-C/CompatHelper.jl
Automatically update the [compat] entries for your Julia package's dependencies
SebastianM-C/DiffEqBase.jl
The lightweight Base library for shared types and functionality.
SebastianM-C/DiffEqBenchmarks.jl
Benchmarks for the DiffEq Solvers
SebastianM-C/DiffEqGPU.jl
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
SebastianM-C/DynamicExpressions.jl
Ridiculously fast symbolic expressions
SebastianM-C/ElectrochemicalMeasurements.jl
A data analysis toolkit for electrochemical measurements of supercapacitors
SebastianM-C/lab_template
SebastianM-C/LinearSolve.jl
LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
SebastianM-C/Lux.jl
Explicitly Parameterized Neural Networks in Julia
SebastianM-C/LuxCore.jl
LuxCore.jl defines the abstract layers for Lux. Allows users to be compatible with the entirely of Lux.jl without having such a heavy dependency.
SebastianM-C/ModelingToolkit.jl
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
SebastianM-C/ModelingToolkitStandardLibrary.jl
A standard library of components to model the world and beyond
SebastianM-C/NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
SebastianM-C/Optimization.jl
Local, global, and beyond optimization for scientific machine learning (SciML)
SebastianM-C/OrdinaryDiffEq.jl
DiffEq solvers for ordinary differential equations
SebastianM-C/PICDataStructures.jl
Data structures for Particle-in-Cell codes
SebastianM-C/RecursiveArrayTools.jl
Tools for easily handling objects like arrays of arrays and deeper nestings
SebastianM-C/RegistryCI.jl
Continuous integration (CI) for Julia package registries. Includes automated testing and automatic merging of pull requests.
SebastianM-C/SBMLToolkit.jl
SBML differential equation and chemical reaction model (Gillespie simulations) for Julia's SciML ModelingToolkit
SebastianM-C/SciMLBase.jl
The Base interface of the SciML ecosystem
SebastianM-C/StructuralIdentifiability.jl
Fast and automatic structural identifiability software for ODE systems
SebastianM-C/Sundials.jl
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner
SebastianM-C/swarm-monitoring
Docker swarm monitoring with Prometheus and Grafana
SebastianM-C/SymbolicRegression.jl
Distributed High-Performance Symbolic Regression in Julia
SebastianM-C/Symbolics.jl
Symbolic programming for the next generation of numerical software