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SciML@JuliaCon 2022 LinearSolve.jl: because A\b is not good enough | ChrisRackauckas | JuliaCon 2022 youtube.com/watch?v=JWI34_…

SciML@JuliaCon 2022 HighDimPDE.jl: A Julia package for solving high-dimensional PDEs | Victor Boussange | JuliaCon 2022 youtube.com/watch?v=4sXqGh…

SciML@JuliaCon 2022 Adaptive Radial Basis Function Surrogates in Julia | Ranjan Anantharaman | JuliaCon 2022 youtube.com/watch?v=3ncvAj…

SciML@JuliaCon 2022 Lux.jl: Explicit Parameterization of Neural Networks in Julia | Avik Pal | JuliaCon 2022 youtube.com/watch?v=5jF-c_…

SciML@JuliaCon 2022 Universal Differential Equation models with wrong assumptions | Luca Reale | JuliaCon 2022 youtube.com/watch?v=lCDrCq…

SciML@JuliaCon 2022 Using SciML to predict the time evolution of a complex network. | Andre Macleod | JuliaCon 2022 youtube.com/watch?v=EstpgV…

SciML@JuliaCon 2022 Exploring audio circuits with ModelingToolkit.jl | George Gkountouras | JuliaCon 2022 youtube.com/watch?v=3DfVow…

SciML@JuliaCon 2022 How to debug Julia simulation codes (ODEs, optimization, etc.!) | ChrisRackauckas | JuliaCon 2022 youtube.com/watch?v=g-iOOh…

SciML@JuliaCon 2022 Fast optimization via randomized numerical linear algebra | Theo Diamandis | JuliaCon 2022 youtube.com/watch?v=aVw-T7…

SciML@JuliaCon 2022 GeneDrive.jl: Simulate and Optimize Biological Interventions | Valeri Vasquez | JuliaCon 2022 youtube.com/watch?v=p0tnGC…

SciML@JuliaCon 2022 How to recover models from data using DataDrivenDiffEq.jl | Carl Julius Martensen | JuliaCon 2022 youtube.com/watch?v=26bHtR…

SciML@JuliaCon 2022 Modeling Instron's Crash Simulation System with ModelingToolkit.jl | Bradley Carman | JuliaCon 2022 youtube.com/watch?v=ChwKqr…

SciML@JuliaCon 2022 Automated PDE Solving in Julia with MethodOfLines.jl | Alex Jones | JuliaCon 2022 youtube.com/watch?v=8gLhaW…

SciML@JuliaCon 2022 FdeSolver.jl: Solving fractional differential equations | Moein Khalighi | JuliaCon 2022 youtube.com/watch?v=FLB-qS…

SciML@JuliaCon 2022 Differentiable Earth system models in Julia | JuliaCon 2022 | Ludovic Räss, Boris Kaus, Julien Le Sommer, Nora Loose, Mathieu Morlighem, Chris Hill, Sarah Williamson, Valentin/Billy, Michel/Krishna, Chris Rackauckas youtube.com/watch?v=K2VtJe…

SciML@JuliaCon 2022 Modeling of Chemical Reaction Networks using Catalyst.jl | JuliaCon 2022 youtube.com/watch?v=tVfxT0…

New paper by Vaibhav Dixit and Chris Rackauckas on a #julialang #sciml library for Global Sensitivity Analysis (GSA)!

Are you interested in SciMLCon 2023? Well we are too, and we're interested in finding out what would make it even better than last year! Please take this survey to share your thoughts: form.jotform.com/222333194908053

Overhauled error messages make it easy to understand incorrect inputs. Major expansions to docstrings, consistent use of style guides, and new #julialang packages for neural operators (DeepONets, Fourier Neural Operators)? See the #sciml ecosystem update! sciml.ai/news/2022/10/0…

Shapley values, a method of explainable Machine Learning (ML), are now in GlobalSensitivity.jl #julialang #sciml. Shapley Effects provide a robust methodology for quantifying the influence of input variables on model outputs. Shapley on Neural ODEs: lnkd.in/gCqRczvB.