#sciml search results
Scientific Modeling Cheatsheet: SciML has published a quick reference cheatsheet translating hundreds of functions between Julia, Python and MATLAB. Click here for more. sciml.github.io/Scientific_Mod… #JuliaLang #SciML #Python #MATLAB #ScientificComputing #DataScience #Cheatsheet…
Check out the latest #Julialang Dispatch Podcast! This episode goes over the changes to the Julia language, its standard libraries, and the main changes in the package ecosystem (#sciml, JuMP, etc.) that occurred over the summer. youtube.com/watch?v=q3_W7a…
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YouTube
This Month in Julia World - August 2025 | JuliaCon Recap & Community...
Newton's method is not efficient for automatic differentiation! Here's a quick explanation as a #sciml fun fact of the day #julialang #differentiableprogramming #automaticdifferentiation
Quoted in @Nature article "Is AI leading to a reproducibility crisis in science?" by @philipcball, I may sound a bit harsh, but it's the truth… #SciML #reproducibility
Hello #FAU. Thanks for the quick plan to host me and letting me present our exciting mathematics of ML in infinite-dimensions, #operatorlearning. #sciML Their "Pattern Recognition Laboratory" is completing 50 years! 💥
Learning Building Thermal Dynamics using Neural State Space Models in NeuroMANCER. Colab example: colab.research.google.com/github/pnnl/ne… Paper: sciencedirect.com/science/articl… Neuromancer SciML library: github.com/pnnl/neuromanc… #SciML #PIML #NSSM #dynamics #themalsystem #building #energy #openrouce
From perception to reasoning—AI is entering a new era. Fujitsu’s #DevSummit keynote explores how #SciML, #AI surrogates & #oneAPI are driving scalable, high-performance, trustworthy AI. Watch now: bit.ly/4qnek5V #UXLFoundation
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Accelerating Scientific ML with FUJITSU-MONAKA: Towards Energy-Effi...
Very excited to share our work on "Science in the Age of Foundation Models", where we discuss applications of foundation models in time series forecasting and PDEs including weather forecasting and aerodynamics. #sciml #pdes #cfd #amazonscience
Foundation models show promise for scientific computing, but adoption lags behind language and vision applications. Amazon researchers reveal what’s needed: physical-constraint satisfaction, uncertainty quantification, and specialized forecasting techniques.
MIT Julia Lab: looking for postdoctoral researchers in #julialang open source software development, scientific machine learning (#SciML), and systems biological / pharmacological modeling (#QSP) for research in equation discovery for large stiff systems. julia.mit.edu/projects/#post…
Learning Stable Deep Koopman Operators in Neuromancer. Colab: colab.research.google.com/github/pnnl/ne… Neuromancer library: github.com/pnnl/neuromanc… #Pytorch #SciML #Koopman #PNNL #opensource #dynamicalsystems
📣New paper alert: "Verification and Validation for Trustworthy Scientific Machine Learning" We propose 16 recommendations to establish trust in #SciML models through rigorous V&V practices adapted from computational science—link in reply #MachineLearning #ComputationalScience
New workshop materials on High-Performance Scientific Modeling with Julia & SciML: • Julia for scientific computing • ODEs/PDEs & numerical methods • Biological systems (Catalyst.jl) • Parameter estimation • Scientific ML & UDEs github.com/SciML/Julia_Mo… #JuliaLang #SciML
Pretty excited about my upcoming talk about #physicsml #sciml at SlovakiaTech Expo/Forum — can’t wait to show folks some mindblowing use cases of AI-driven approaches to engineering and science, and the future where we’re heading!
Great Talk on #SciML by @ChrisRackauckas at @JuliaConOrg - including how Julia was used in creating the Moderna vaccine
Complex system modeling often requires stitching together fragmented tools. #Dyad, powered by Julia and #SciML, changes this by combining symbolic #modeling, composable libraries, and packages like SatelliteToolbox.jl into a single workflow. From orbital mechanics to power…
An updated version of our slides on necessary conditions for #SciML, - and more specially, "Machine Learning in Function Spaces/Infinite Dimensions". Its all about the 2 key inequalities we derive on slides 27 and 33. Both come via similar proofs. github.com/Anirbit-AI/Sli…
Check out the latest #Julialang Dispatch Podcast! This episode goes over the changes to the Julia language, its standard libraries, and the main changes in the package ecosystem (#sciml, JuMP, etc.) that occurred over the summer. youtube.com/watch?v=q3_W7a…
youtube.com
YouTube
This Month in Julia World - August 2025 | JuliaCon Recap & Community...
Watch Dyad's AI agent build a complete thermal model from just an image! Picture -> validated DAEs in minutes. Features: Auto parameter generation, model optimization, custom animations. All with production-ready Julia code. youtu.be/eKLDVCkJC1s #dyad #julialang #sciml
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Generating a Coffee Cup Thermal Model from a Schematic
#Dyad #SciML tutorial! Use Dyad's graphical/textual #acausal system to build models from validated model components and transform into your #digitaltwin! #Dyad = component-based modeling tool (e.g. #Modelica, #Amesim, #Simulink) + AI/ML autocomplete! youtube.com/watch?v=ttQIE3…
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Dyad SciML Tutorial: Model Discovery with Universal Differential...
Scientific Modeling Cheatsheet: SciML has published a quick reference cheatsheet translating hundreds of functions between Julia, Python and MATLAB. Click here for more. sciml.github.io/Scientific_Mod… #JuliaLang #SciML #Python #MATLAB #ScientificComputing #DataScience #Cheatsheet…
From perception to reasoning—AI is entering a new era. Fujitsu’s #DevSummit keynote explores how #SciML, #AI surrogates & #oneAPI are driving scalable, high-performance, trustworthy AI. Watch now: bit.ly/4qnek5V #UXLFoundation
youtube.com
YouTube
Accelerating Scientific ML with FUJITSU-MONAKA: Towards Energy-Effi...
Newton's method is not efficient for automatic differentiation! Here's a quick explanation as a #sciml fun fact of the day #julialang #differentiableprogramming #automaticdifferentiation
High-Performance Scientific #Modeling with Julia and SciML: This workshop offers in-depth training on advanced scientific computing techniques using the Julia programming language and the SciML (Scientific Machine Learning) ecosystem. github.com/SciML/Julia_Mo… #JuliaLang #SciML…
Excited to share our new research on ASNO—Adaptive Scientific Neural Operator! 📄 We've designed a novel model for efficient scientific machine learning. Check out the paper: iopscience.iop.org/article/10.108… #ML #AI #SciML #NeuralOperator
SciML Developer Chat Episode 1: Base Splits and Symbolics Precompilation Welcome to the first episode of the SciML Dev Chat! We discuss the latest developments in the #SciML (Scientific Machine Learning) ecosystem for #julialang! youtu.be/0yQ4aZ-ABhY
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SciML Developer Chat Episode 1: Trimming Support and Symbolics...
MIT Julia Lab: looking for postdoctoral researchers in #julialang open source software development, scientific machine learning (#SciML), and systems biological / pharmacological modeling (#QSP) for research in equation discovery for large stiff systems. julia.mit.edu/projects/#post…
Claude code sucks... but it's still very useful! Check out this blog post that details how Claude is deployed to solve problems in the #Julialang #SciML open source scientific computing infrastructure. stochasticlifestyle.com/claude-code-in… #llm #vibecoding #physics #opensource #oss
stochasticlifestyle.com
Claude Code sucks but is still useful: experiences maintaining Julia's SciML scientific computing...
Claude Code sucks but is still useful: experiences maintaining Julia’s SciML scientific computing infrastructure So it’s pretty public that for about a month now I’ve had 32 processes setup on one of...
Very excited to share our work on "Science in the Age of Foundation Models", where we discuss applications of foundation models in time series forecasting and PDEs including weather forecasting and aerodynamics. #sciml #pdes #cfd #amazonscience
Foundation models show promise for scientific computing, but adoption lags behind language and vision applications. Amazon researchers reveal what’s needed: physical-constraint satisfaction, uncertainty quantification, and specialized forecasting techniques.
New workshop materials on High-Performance Scientific Modeling with Julia & SciML: • Julia for scientific computing • ODEs/PDEs & numerical methods • Biological systems (Catalyst.jl) • Parameter estimation • Scientific ML & UDEs github.com/SciML/Julia_Mo… #JuliaLang #SciML
📢 Calling for (4-page) workshop papers on #differentiable programming and #SciML. This is a great opportunity to showcase your work or work in progress alongside keynote presentations by Petros Koumoutsakos, @PatrickKidger, @thuereyGroup & Astrid Walle.
🚨🚨🚨 Call for papers alert 🚨🚨🚨 The "Differentiable Systems and Scientific Machine Learning" workshop at the 1st EurIPS conference is now accepting submissions! Let's explore the intersection of differentiable programming and SciML together. differentiable-systems.github.io/workshop-eurip…
DifferentialEquations.jl is many things, and lots of people only use a small portion of it. Check out the JuliaCon 2025 workshop: introduces many aspects of the packages that the developers feel are underutilized and under-understood! #julialang #sciml youtube.com/watch?v=lSGFAm…
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A Deep Dive Into DifferentialEquations.jl | JuliaCon Global 2025 |...
Check out the JuliaCon workshop SciML in Fluid Dynamics (CFD): Surrogates of Weather Models. Go into depth on all of the major surrogate architectures and give them a try on the weather model challenge problem! youtube.com/watch?v=PfRxU2… #julialang #juliacon #sciml
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SciML in Fluid Dynamics (CFD): Surrogates of Weather Models |...
Sundials.jl v5.0: Update to SUNDIALS v7 and Improved DAE Initialization A major update that brings significant improvements to differential-algebraic equation (DAE) solving and upgrades to the latest Sundials C library sciml.ai/news/2025/09/1… #julialang #sciml #sundials #dae
Mixed precision and automatic GPU offloading for Newton solves and stiff ODE solvers has now landed thanks to improvements in LinearSolve.jl. Run LinearSolveAutotune.jl so that things like usage of GPUs in #julialang #sciml becomes automatic! sciml.ai/news/2025/09/0…
New Symbolic-Numeric algorithm which uses rational polynomial interpolation mixed with differential algebra in order to give a highly robust method for parameter estimation and solving inverse problems on ODEs. #julialang #sciml #symbolicnumeric #ode sciencedirect.com/science/articl…
Solution of nonlinear PDEs is not just a simple interpolation (linear combination) of solutions of the same PDE for different parameters, BCs and ICs. Even for linear PDEs it does not work as soon as we change the domain and BCs. This is what #SciML people don't understand.
Scientific Modeling Cheatsheet: SciML has published a quick reference cheatsheet translating hundreds of functions between Julia, Python and MATLAB. Click here for more. sciml.github.io/Scientific_Mod… #JuliaLang #SciML #Python #MATLAB #ScientificComputing #DataScience #Cheatsheet…
Hello #FAU. Thanks for the quick plan to host me and letting me present our exciting mathematics of ML in infinite-dimensions, #operatorlearning. #sciML Their "Pattern Recognition Laboratory" is completing 50 years! 💥
Learning Building Thermal Dynamics using Neural State Space Models in NeuroMANCER. Colab example: colab.research.google.com/github/pnnl/ne… Paper: sciencedirect.com/science/articl… Neuromancer SciML library: github.com/pnnl/neuromanc… #SciML #PIML #NSSM #dynamics #themalsystem #building #energy #openrouce
I'm honored and excited to join the SIAM Journal on Scientific Computing (SISC) as an associate editor for the new Scientific Machine Learning section starting in 2024. If you're working on exciting SciML research, consider submitting your best work to SISC! #SciML
Quoted in @Nature article "Is AI leading to a reproducibility crisis in science?" by @philipcball, I may sound a bit harsh, but it's the truth… #SciML #reproducibility
Physics simulations? Yes, there's an AI for that. theresanaiforthat.com/ai/siml-ai/ #PhysicsML #SciML
Learning Stable Deep Koopman Operators in Neuromancer. Colab: colab.research.google.com/github/pnnl/ne… Neuromancer library: github.com/pnnl/neuromanc… #Pytorch #SciML #Koopman #PNNL #opensource #dynamicalsystems
Our @stetuned and @fr_regazzoni co-organized with @rozzagroup the Workshop 💡Scientific Machine Learning, emerging topics💡 held at @Sissaschool, #Trieste #SMLET #SciML @mox_lab #DaVittorio
What I have been saying ever since this craze started! Quite a comprehensive study of biases and issues with all things #SciML for CFD. These findings equally apply to other domains. Full paper at arxiv.org/abs/2407.07218 #AI #ML #NeuralNetworks #PINNs #PIML #PEML #PGML
@JuliaConOrg was hectic and amazing. Thank you everyone for the conversations and support. You can see how frantic it was from the wear and tear on the badge, falling off by the end. So many #julialang #sciml workshops and breakouts. I cannot wait for the next one!
Scientific Machine Learning (#SciML) is an emerging field that synergistically blends machine learning and scientific computing based on mechanistic models, usually yielding increased interpretability, performance and data efficiency. (2/11) Image from: frontiersin.org/articles/10.33…
Differentiable Metropolis-Hastings: differentiate through Bayesian estimation to optimize models towards achieving desired probabilistic outcomes, with implementation in #julialang (#sciml) For more information, see arxiv.org/abs/2306.07961
📣New paper alert: "Verification and Validation for Trustworthy Scientific Machine Learning" We propose 16 recommendations to establish trust in #SciML models through rigorous V&V practices adapted from computational science—link in reply #MachineLearning #ComputationalScience
As we predicted years ago, commercial LLMs have become simple statistical surrogates for classical trivial search. On the other hand, in #CriticalIndustries where precision still matters, Scientific Machine Learning continues to dominate real-life use cases. #GenAI vs #SciML
I'm thrilled to share that I've started a Postdoc position @Penn! 🎉🎊 I'll be working with Nat Trask on scientific deep learning and structure-preserving algorithms. Looking forward to learning and contributing to this amazing field with new ideas! #AI4Science #SciML #UPennMEAM
I'll be in Trondheim 2 weeks from now. Anyone local interested in #julialang #sciml should check out the seminar!
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