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The purpose of this page is to demonstrate the various applications where the SciML tools have been employed. If you would like your own work added to this list, please open a pull request.
There are many external libraries which connect and utilize SciML utilities under the hood. The following an incomplete list of software organizations providing domain modeling tools that are built upon SciML. If you would like your institution's tools added to the list, please open a pull request.
CMU+MIT+Citrine: Accelerated Computational Electrochemical Systems Discovery (ACED)
Los Alamos National Lab: Model Analysis & Decision Support (MADS)
New MIT (SciML) Model Could Help Determine Quarantine Measures Needed to Reduce COVID-19’s Spread
SciML Software (through Pumas) is utilized in an FDA-approved submission
MIT-led team to develop (SciML) software to help forecast space storms
The Air Force’s Latest GPS Alternative: Earth’s Magnetic Fields (research powered by SciML)
Cornell Chronicle: Digital ‘virus’ helps researchers map potential spread
Phys.org: Digital 'virus' helps researchers map potential spread
latronet.gr: Χαρτογράφηση εξάπλωσης CoViD-19 με κινητό τηλέφωνο
Popular Deep Learning Frameworks: An Overview (DiffEqFlux.jl mentioned)
ZDNet: Could a neural network have predicted this pandemic’s impact?
UQ News: A mathematical framework could help safely ease social distancing
MIT News: Model quantifies the impact of quarantine measures on Covid-19’s spread
COVID-19 simulator could help track virus spread as restrictions eased
The Brazilian National Institute for Space Research (INPE) plans space missions with SciML
JaxEnter: Machine learning meets math: Solve differential equations with new Julia library
Julia (SciML) is awarded funded through the ARPA-E DIFFERENTIATE Program
The Koopman Operator in Systems and Control
"All simulations have been performed in Julia, with additional Julia packages: LinearAlgebra.jl, Random.jl, Plots.jl, Lasso.jl, DifferentialEquations.jl"
Neural ODE for Reinforcement Learning and Nonlinear Optimal Control: Cartpole Problem Revisited
"Modeling control of run-of-river power plant Grønvollfoss" in Julia
GPU-Accelerated ODE Solving in R with Julia, the Language of Libraries
Francesco Martinuzzi: Google Summer of Code 2020 Final Report
High weak order solvers and adjoint sensitivity analysis for stochastic differential equations
Francesco Martinuzzi: GSoC week 11: Gated Recurring Unit-based reservoir
Francesco Martinuzzi: GSoC week 10: Reservoir Memory Machines
Francesco Martinuzzi: GSoC week 9: Cycle Reservoirs with Regular Jumps
Utkarsh's Blog: Second Evaluations (Parallel Extrapolation Methods)
Physics-informed neural networks (PINNs) solver on Julia. GSoC 2020. Second evaluation.
Ludovico: July deliverables: Two new surrogates methods and benchmarking
Francesco Martinuzzi: GSoC week 7: Reservoir Computing with Cellular Automata Part 1
Francesco Martinuzzi: GSoC week 6: minimum complexity echo state network
Kirill Zubov: Physics-informed neural networks (PINNs) solvers on Julia
Sebastian Callh personal blog: Forecasting the weather with neural ODEs
Utkarsh's Blog: Community Bonding & First Evaluation (BDF & NDF methods)
Ludovico: From JSOC to GSOC: a new beginning with Surrogates.jl
Francesco Martinuzzi: GSoC week 3: Echo State Gaussian Processes
SCIML: LOGICIELS LIBRES POUR L'APPRENTISSAGE MACHINE SCIENTIFIQUE
Francesco Martinuzzi: GSoC week 2: Support Vector Regression in Echo State Networks
Frank Schäfer: GSoC 2020: High weak order SDE solvers and their utility in neural SDEs
Modeling pandemics subject to stochastic uncertainties – A polynomial chaos approach
Francesco Martinuzzi: GSoC week 1: lasso, Elastic Net and Huber loss
Modelling and data analysis tools to study the 2020 COVID-19 outbreak
Kevin Hannay: Differential Equations as a Neural Network Layers
Safe Blues — The Measurement Tool for Responsible Easing of Social Distancing
Per-Olof Persson and Robert Sweeney Blanco: The DifferentialEquations Package
Current status of neural differential equations and the importance of language
Phylodynamics of SARS-CoV-2, Simon Frost (Microsoft Health Futures)
Francesco Martinuzzi: A brief introduction to Reservoir Computing
Nicolau Leal Werneck: Fitting the SIR model to Covid-19 fatality data
StochasticLifestyle: Recent advancements in differential equation solver software
StochasticLifestyle: A Collection of Jacobian Sparsity Acceleration Tools for Julia
StochasticLifestyle: The Essential Tools of Scientific Machine Learning (Scientific ML)
StochasticLifestyle: Neural Jump SDEs (Jump Diffusions) and Neural PDEs
JuliaLang: DiffEqFlux.jl – A Julia Library for Neural Differential Equations
StochasticLifestyle: Some State of the Art Packages in Julia v1.0
Mathieu Besançon: Winter warm-up: toy models for heat exchangers
UCI Data Science Initiative: A Quick Tour of DifferentialEquations.jl
StochasticLifestyle: Why Numba and Cython are not substitutes for Julia
Ronan Chagas: Using julia to simulate systems composed of continuous and discrete parts
StochasticLifestyle: Solving Systems of Stochastic PDEs and using GPUs in Julia
JuliaLang: GSoC 2017 : A Wrapper for the FEniCS Finite Element Toolbox
JuliaLang: GSoC 2017: Efficient Discretizations of PDE Operators
StochasticLifestyle: Some Fun With Julia Types: Symbolic Expressions in the ODE Solver
JuliaLang: GSoC 2017: Native Julia second order ODE and BVP solvers
Yiannis Simillides blog: FEniCS.jl: Second "Approximate" Month
Yiannis Simillides blog: FEniCS.jl: First "Approximate" Month
Mathieu Besançon: DifferentialEquations.jl - part 2: decision from the model
Mathieu Besançon: Getting started with DifferentialEquations.jl