corpus.blog
41554 blogs · [ { "id": "01a087e6-9edc-7041-8bd5-f134a179a9fd", "title": "What Agentic AI “Vibe Coding” In The Hands Of Actual Programmers / Engineers", "url": "https://www.stochasticlifestyle.com/what-agentic-ai-vibe-coding-in-the-hands-of-actual-programmers-engineers/", "published_at": "2026-02-12T12:24:22+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a1bbaa1c", "title": "Why Julia’s GPU Accelerated ODE Solvers are 20x-100x Faster than Jax and PyTorch", "url": "https://www.stochasticlifestyle.com/why-julias-gpu-accelerated-ode-solvers-are-20x-100x-faster-than-jax-and-pytorch/", "published_at": "2026-01-11T14:18:00+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a24e870a", "title": "Claude Code sucks but is still useful: experiences maintaining Julia’s SciML scientific computing infrastructure", "url": "https://www.stochasticlifestyle.com/claude-code-in-scientific-computing-experiences-maintaining-julias-sciml-infrastructure/", "published_at": "2025-10-06T06:20:56+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a30478df", "title": "Implicit ODE Solvers Are Not Universally More Robust than Explicit ODE Solvers, Or Why No ODE Solver is Best", "url": "https://www.stochasticlifestyle.com/implicit-ode-solvers-are-not-universally-more-robust-than-explicit-ode-solvers-or-why-no-ode-solver-is-best/", "published_at": "2025-09-04T07:11:02+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a3b0091b", "title": "A Guide to Gen AI / LLM Vibecoding for Expert Programmers", "url": "https://www.stochasticlifestyle.com/a-guide-to-gen-ai-llm-vibecoding-for-expert-programmers/", "published_at": "2025-08-22T14:36:33+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a3cc4497", "title": "Machine learning with hard constraints: Neural Differential-Algebraic Equations (DAEs) as a general formalism", "url": "https://www.stochasticlifestyle.com/machine-learning-with-hard-constraints-neural-differential-algebraic-equations-daes-as-a-general-formalism/", "published_at": "2025-06-03T18:20:49+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a4b69e75", "title": "How chaotic is chaos? How some AI for Science / SciML papers are overstating accuracy claims", "url": "https://www.stochasticlifestyle.com/how-chaotic-is-chaos-how-some-ai-for-science-sciml-papers-are-overstating-accuracy-claims/", "published_at": "2025-05-26T13:00:39+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a5417ba5", "title": "A Hands on Introduction to Applied Scientific Machine Learning / Physics-Informed Learning", "url": "https://www.stochasticlifestyle.com/a-hands-on-introduction-to-applied-scientific-machine-learning-physics-informed-learning/", "published_at": "2025-05-11T10:23:37+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a5de75a2", "title": "Open Source Component-Based Modeling with ModelingToolkit", "url": "https://www.stochasticlifestyle.com/open-source-component-based-modeling-with-modelingtoolkit/", "published_at": "2025-05-05T11:37:32+00:00" }, { "id": "01a087e6-9edc-7041-8bd5-f134a5ff369b", "title": "The Numerical Analysis of Differentiable Simulation: Automatic Differentiation Can Be Incorrect", "url": "https://www.stochasticlifestyle.com/the-numerical-analysis-of-differentiable-simulation-automatic-differentiation-can-be-incorrect/", "published_at": "2025-04-20T03:55:49+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f3836401", "title": "JuliaSim: Building a Product which improves Open Source Sustainability", "url": "https://www.stochasticlifestyle.com/juliasim-building-a-product-which-improves-open-source-sustainability/", "published_at": "2025-01-26T23:18:04+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f41acf0b", "title": "Differences Between Methods for Solving Stiff ODEs", "url": "https://www.stochasticlifestyle.com/differences-between-methods-for-solving-stiff-odes/", "published_at": "2024-04-06T20:29:00+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f44e1a37", "title": "Symbolic-Numerics: how compiler smarts can help improve the performance of numerical methods (nonlinear solvers in Julia)", "url": "https://www.stochasticlifestyle.com/symbolic-numerics-how-compiler-smarts-can-help-improve-the-performance-of-numerical-methods-nonlinear-solvers-in-julia/", "published_at": "2024-02-13T10:06:17+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f4adde3b", "title": "Semantic Versioning (Semver) is flawed, and Downgrade CI is required to fix it", "url": "https://www.stochasticlifestyle.com/semantic-versioning-semver-is-flawed-and-downgrade-ci-is-required-to-fix-it/", "published_at": "2024-02-11T12:44:34+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f4c6e2fe", "title": "ChatGPT performs better on Julia than Python (and R) for Large Language Model (LLM) Code Generation. Why?", "url": "https://www.stochasticlifestyle.com/chatgpt-performs-better-on-julia-than-python-and-r-for-large-language-model-llm-code-generation-why/", "published_at": "2023-11-19T15:57:36+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f59ea542", "title": "DDPS Seminar Talk: Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous models", "url": "https://www.stochasticlifestyle.com/ddps-seminar-talk-generalizing-scientific-machine-learning-and-differentiable-simulation-beyond-continuous-models/", "published_at": "2023-11-12T11:54:03+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f5a6d440", "title": "Summary of Julia Plotting Packages", "url": "https://www.stochasticlifestyle.com/summary-of-julia-plotting-packages/", "published_at": "2023-06-17T14:23:29+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f5cee17c", "title": "Integrating equation solvers with probabilistic programming through differentiable programming", "url": "https://www.stochasticlifestyle.com/integrating-equation-solvers-with-probabilistic-programming-through-differentiable-programming/", "published_at": "2022-11-24T01:04:59+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f6860e44", "title": "Direct Automatic Differentiation of (Differential Equation) Solvers vs Analytical Adjoints: Which is Better?", "url": "https://www.stochasticlifestyle.com/direct-automatic-differentiation-of-solvers-vs-analytical-adjoints-which-is-better/", "published_at": "2022-10-11T07:09:53+00:00" }, { "id": "01a0d2e5-81a6-70f8-bddb-3900f70de397", "title": "Is Differentiable Programming Actually Necessary? Can’t you just train the neural networks separately?", "url": "https://www.stochasticlifestyle.com/is-differentiable-programming-actually-necessary-cant-you-just-train-separately/", "published_at": "2022-10-04T07:38:56+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e2ed9e5ed", "title": "Accurate and Efficient Physics-Informed Learning Through Differentiable Simulation (ASA Seminar Talk)", "url": "https://www.stochasticlifestyle.com/accurate-and-efficient-physics-informed-learning-through-differentiable-simulation-asa-seminar-talk/", "published_at": "2022-07-14T09:58:09+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e2fa64de7", "title": "Keynote: New Horizons in Modeling and Simulation with Julia (Modelica Conference 2021)", "url": "https://www.stochasticlifestyle.com/keynote-new-horizons-in-modeling-and-simulation-with-julia-modelica-conference-2021/", "published_at": "2022-06-25T18:11:28+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e2fec74d7", "title": "Composing Modeling and Simulation with Julia (2021 Modelica Conference)", "url": "https://www.stochasticlifestyle.com/composing-modeling-and-simulation-with-julia-2021-modelica-conference/", "published_at": "2022-04-08T11:30:11+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e3081f331", "title": "Engineering Trade-Offs in Automatic Differentiation: from TensorFlow and PyTorch to Jax and Julia", "url": "https://www.stochasticlifestyle.com/engineering-trade-offs-in-automatic-differentiation-from-tensorflow-and-pytorch-to-jax-and-julia/", "published_at": "2021-12-25T11:50:10+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e3092ad5c", "title": "Improved ForwardDiff.jl Stacktraces With Package Tags", "url": "https://www.stochasticlifestyle.com/improved-forwarddiff-jl-stacktraces-with-package-tags/", "published_at": "2021-12-19T13:41:34+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e3165956c", "title": "The Use and Practice of Scientific Machine Learning", "url": "https://www.stochasticlifestyle.com/the-use-and-practice-of-scientific-machine-learning/", "published_at": "2021-11-18T15:03:34+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e3212db87", "title": "When does the mean and variance define an SDE?", "url": "https://www.stochasticlifestyle.com/when-does-the-mean-and-variance-define-an-sde/", "published_at": "2021-11-01T17:51:07+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e32f66d70", "title": "Learning Epidemic Models That Extrapolate, AI4Pandemics", "url": "https://www.stochasticlifestyle.com/learning-epidemic-models-that-extrapolate-ai4pandemics/", "published_at": "2021-07-25T11:42:40+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e331f2aab", "title": "Useful Algorithms That Are Not Optimized By Jax, PyTorch, or Tensorflow", "url": "https://www.stochasticlifestyle.com/useful-algorithms-that-are-not-optimized-by-jax-pytorch-or-tensorflow/", "published_at": "2021-07-21T10:42:12+00:00" }, { "id": "01a0d2e5-ff6e-70ca-a43b-c35e33233059", "title": "ModelingToolkit, Modelica, and Modia: The Composable Modeling Future in Julia", "url": "https://www.stochasticlifestyle.com/modelingtoolkit-modelica-and-modia-the-composable-modeling-future-in-julia/", "published_at": "2021-04-19T19:09:21+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397c51bd55", "title": "Generalizing Automatic Differentiation to Automatic Sparsity, Uncertainty, Stability, and Parallelism", "url": "https://www.stochasticlifestyle.com/generalizing-automatic-differentiation-to-automatic-sparsity-uncertainty-stability-and-parallelism/", "published_at": "2021-03-10T13:43:52+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397cf2b369", "title": "JuliaCall Update: Automated Julia Installation for R Packages", "url": "https://www.stochasticlifestyle.com/juliacall-update-automated-julia-installation-for-r-packages/", "published_at": "2021-01-18T07:17:00+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397d4db8c3", "title": "GPU-Accelerated ODE Solving in R with Julia, the Language of Libraries", "url": "https://www.stochasticlifestyle.com/gpu-accelerated-ode-solving-in-r-with-julia-the-language-of-libraries/", "published_at": "2020-08-24T12:52:12+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397e06ab7d", "title": "COVID-19 Epidemic Mitigation via Scientific Machine Learning (SciML)", "url": "https://www.stochasticlifestyle.com/covid-19-epidemic-mitigation-via-scientific-machine-learning-sciml/", "published_at": "2020-07-07T12:11:20+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397e12e593", "title": "Cheap But Effective: Instituting Effective Pandemic Policies Without Knowing Who’s Infected", "url": "https://www.stochasticlifestyle.com/cheap-but-effective-instituting-effective-pandemic-policies-without-knowing-whos-infected/", "published_at": "2020-07-02T19:33:24+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397e51f93a", "title": "Glue AD for Full Language Differentiable Programming", "url": "https://www.stochasticlifestyle.com/glue-ad-for-full-language-differentiable-programming/", "published_at": "2020-06-15T07:43:03+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397f153445", "title": "Generalized Physics-Informed Learning through Language-Wide Differentiable Programming (Video)", "url": "https://www.stochasticlifestyle.com/generalized-physics-informed-learning-through-language-wide-differentiable-programming-video/", "published_at": "2020-03-31T15:22:46+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f8397f312d2a", "title": "Universal Differential Equations for Scientific Machine Learning (Video)", "url": "https://www.stochasticlifestyle.com/universal-differential-equations-for-scientific-machine-learning-video/", "published_at": "2020-03-06T21:36:50+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f83980225149", "title": "Scientific Machine Learning: Interpretable Neural Networks That Accurately Extrapolate From Small Data", "url": "https://www.stochasticlifestyle.com/how-to-train-interpretable-neural-networks-that-accurately-extrapolate-from-small-data/", "published_at": "2020-01-14T15:19:55+00:00" }, { "id": "01a0d2e6-7809-7306-8706-f83980c2cf2d", "title": "How Inexact Models and Scientific Machine Learning Can Guide Decision Making in Quantitative Systems Pharmacology", "url": "https://www.stochasticlifestyle.com/how-inexact-models-can-guide-decision-making-in-quantitative-systems-pharmacology/", "published_at": "2019-12-15T14:51:56+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-53215e2a9de1", "title": "Recent advancements in differential equation solver software", "url": "https://www.stochasticlifestyle.com/recent-advancements-in-differential-equation-solver-software/", "published_at": "2019-10-16T18:46:10+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-53215ea1c142", "title": "A Collection of Jacobian Sparsity Acceleration Tools for Julia", "url": "https://www.stochasticlifestyle.com/a-collection-of-jacobian-sparsity-acceleration-tools-for-julia/", "published_at": "2019-10-06T11:39:54+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-53215ecfeaab", "title": "Developing Julia Packages", "url": "https://www.stochasticlifestyle.com/developing-julia-packages/", "published_at": "2019-10-04T13:51:44+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-53215fc1be29", "title": "When do micro-optimizations matter in scientific computing?", "url": "https://www.stochasticlifestyle.com/when-do-micro-optimizations-matter-in-scientific-computing/", "published_at": "2019-09-03T12:08:20+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-532160b4dbcd", "title": "The Essential Tools of Scientific Machine Learning (Scientific ML)", "url": "https://www.stochasticlifestyle.com/the-essential-tools-of-scientific-machine-learning-scientific-ml/", "published_at": "2019-08-20T14:42:58+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-53216177167f", "title": "Scientific AI: Domain 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"2018-10-29T13:45:07+00:00" }, { "id": "01a0d2e6-ebdd-70e2-b5f1-532164b19b08", "title": "Some State of the Art Packages in Julia v1.0", "url": "https://www.stochasticlifestyle.com/some-state-of-the-art-packages-in-julia-v1-0/", "published_at": "2018-08-27T15:05:26+00:00" }, { "id": "01a0d2e7-6024-71d2-b959-a4fcbaa4d787", "title": "PuMaS.jl: Pharmaceutical Modeling and Simulation Engine", "url": "https://www.stochasticlifestyle.com/pumas-jl-pharmaceutical-modeling-and-simulation-engine/", "published_at": "2018-08-13T18:31:38+00:00" }, { "id": "01a0d2e7-6024-71d2-b959-a4fcbb55c7ef", "title": "Solving Partial Differential Equations with Julia", "url": "https://www.stochasticlifestyle.com/solving-partial-differential-equations-with-julia/", "published_at": "2018-08-08T06:03:11+00:00" }, { "id": "01a0d2e7-6024-71d2-b959-a4fcbbfceccf", "title": "Why Numba and Cython are not substitutes for Julia", "url": 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"DifferentialEquations.jl 3.0 and a Roadmap for 4.0", "url": "https://www.stochasticlifestyle.com/differentialequations-jl-3-0-roadmap-4-0/", "published_at": "2017-10-30T19:55:01+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e2464d911439", "title": "I Like Julia Because It Scales and Is Productive: Some Insights From A Julia Developer", "url": "https://www.stochasticlifestyle.com/like-julia-scales-productive-insights-julia-developer/", "published_at": "2017-10-13T12:58:00+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e2464e816610", "title": "A Comparison Between Differential Equation Solver Suites In MATLAB, R, Julia, Python, C, Mathematica, Maple, and Fortran", "url": "https://www.stochasticlifestyle.com/comparison-differential-equation-solver-suites-matlab-r-julia-python-c-fortran/", "published_at": "2017-09-26T01:51:09+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e2464f760fa5", "title": "Video Introduction to DifferentialEquations.jl", "url": "https://www.stochasticlifestyle.com/video-introduction-differentialequations-jl/", "published_at": "2017-07-07T17:41:22+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e2465057e354", "title": "Type-Dispatch Design: Post Object-Oriented Programming for Julia", "url": "https://www.stochasticlifestyle.com/type-dispatch-design-post-object-oriented-programming-julia/", "published_at": "2017-05-29T12:57:30+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e24650fb758c", "title": "Video Blog: Developing and Editing Julia Packages", "url": "https://www.stochasticlifestyle.com/video-blog-developing-editing-julia-packages/", "published_at": "2017-05-16T20:37:57+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e246519ab191", "title": "DifferentialEquations.jl 2.0: State of the Ecosystem", "url": "https://www.stochasticlifestyle.com/differentialequations-jl-2-0-state-ecosystem/", "published_at": "2017-05-08T12:13:30+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e246525b80f5", "title": "Some Fun With Julia Types: Symbolic Expressions in the ODE Solver", "url": "https://www.stochasticlifestyle.com/fun-julia-types-symbolic-expressions-ode-solver/", "published_at": "2017-05-04T05:57:04+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e24652cad2da", "title": "Building a Web App in Julia: DifferentialEquations.jl Online", "url": "https://www.stochasticlifestyle.com/building-web-app-julia-differentialequations-jl-online/", "published_at": "2017-01-17T21:35:15+00:00" }, { "id": "01a0d2e7-b626-708f-9b9c-e246534f8fe5", "title": "6 Months of DifferentialEquations.jl: Where We Are and Where We Are Going", "url": "https://www.stochasticlifestyle.com/6-months-differentialequations-jl-going/", "published_at": "2016-12-15T06:41:26+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d76f88e943", "title": "Modular Algorithms for Scientific Computing in Julia", "url": "https://www.stochasticlifestyle.com/modular-algorithms-scientific-computing-julia/", "published_at": "2016-12-07T16:55:56+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d76fa8f349", "title": "7 Julia Gotchas and How to Handle Them", "url": "https://www.stochasticlifestyle.com/7-julia-gotchas-handle/", "published_at": "2016-10-04T00:50:56+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d7704fd353", "title": "Introducing DifferentialEquations.jl", "url": "https://www.stochasticlifestyle.com/introducing-differentialequations-jl/", "published_at": "2016-08-01T14:24:10+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d7711e8c68", "title": "Using Julia’s Type System For Hidden Performance Gains", "url": "https://www.stochasticlifestyle.com/using-julias-type-system-hidden-performance-chunkedarrays-growablearrays-ellipsisnotation/", "published_at": "2016-06-07T20:54:08+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d7715c07ef", "title": "Finalizing Your Julia Package: Documentation, Testing, Coverage, and Publishing", "url": "https://www.stochasticlifestyle.com/finalizing-julia-package-documentation-testing-coverage-publishing/", "published_at": "2016-05-16T20:07:36+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d771ed1a25", "title": "Optimal Number of Workers for Parallel Julia", "url": "https://www.stochasticlifestyle.com/236-2/", "published_at": "2016-04-16T16:58:07+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d771f05d73", "title": "Holding off on Julia for a little bit… you should blog!", "url": "https://www.stochasticlifestyle.com/holding-off-julia-little-bit-blog/", "published_at": "2016-03-28T16:23:51+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d772a06a96", "title": "Benchmarks of Multidimensional Stack Implementations in Julia", "url": "https://www.stochasticlifestyle.com/233-2/", "published_at": "2016-03-20T18:46:33+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d77382f913", "title": "MATLAB 2016a Release Summary for Scientific Computing", "url": "https://www.stochasticlifestyle.com/matlab-2016a-release-summary/", "published_at": "2016-03-15T02:45:05+00:00" }, { "id": "01a0d2e8-01de-722e-a20c-b9d77435c275", "title": "Interfacing with a Xeon Phi via Julia", "url": "https://www.stochasticlifestyle.com/interfacing-xeon-phi-via-julia/", "published_at": "2016-03-04T21:30:17+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-062911a9dd0e", "title": "Multiple-GPU Parallelism on the HPC with Julia", "url": "https://www.stochasticlifestyle.com/multiple-gpu-on-the-hpc-with-julia/", "published_at": "2016-02-28T02:48:55+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-06291230cfe2", "title": "Tutorial for Julia on the HPC with GPUs", "url": "https://www.stochasticlifestyle.com/julia-on-the-hpc-with-gpus/", "published_at": "2016-02-23T06:33:46+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-06291292579e", "title": "Multi-node Parallelism in Julia on an HPC (XSEDE Comet)", "url": "https://www.stochasticlifestyle.com/multi-node-parallelism-in-julia-on-an-hpc/", "published_at": "2016-02-23T05:42:06+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-062912b2f1fc", "title": "Blog Upgraded: A Good Experience With Bluehost", "url": "https://www.stochasticlifestyle.com/blog-is-back-up/", "published_at": "2016-02-23T05:06:31+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-06291336b78e", "title": "Comparison of US HPC Resources", "url": "https://www.stochasticlifestyle.com/comparison-of-us-hpc-resources/", "published_at": "2016-02-20T16:08:22+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-062913df2dab", "title": "Using Julia’s C Interface to Utilize C Libraries", "url": "https://www.stochasticlifestyle.com/using-julias-c-interface-utilize-c-libraries/", "published_at": "2016-02-04T06:58:22+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-06291415fe05", "title": "Setting Variables Element-wise in a Matrix in Mathematica", "url": "https://www.stochasticlifestyle.com/setting-variables-element-wise-in-a-matrix-in-mathematica/", "published_at": "2016-02-02T18:31:02+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-06291457de45", "title": "Simple Parallel Optimization in Mathematica", "url": "https://www.stochasticlifestyle.com/simple-parallel-optimization-in-mathematica/", "published_at": "2016-02-02T02:30:04+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-0629155512c8", "title": "Why is Mathematica Stopping My Long Calculation?", "url": "https://www.stochasticlifestyle.com/why-is-mathematica-stopping-my-long-calculation/", "published_at": "2016-01-30T06:32:19+00:00" }, { "id": "01a0d2e8-5549-71f4-becc-062915593d31", "title": "Julia iFEM3: Solving the Poisson Equation via MATLAB Interfacing", "url": "https://www.stochasticlifestyle.com/julia-ifem3/", "published_at": "2016-01-24T10:32:36+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c31826962", "title": "Julia iFEM 2: Optimizing Stiffness Matrix Assembly", "url": "https://www.stochasticlifestyle.com/julia-ifem2/", "published_at": "2016-01-23T11:21:59+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c319eda5b", "title": "Optimizing .*: Details of Vectorization and Metaprogramming", "url": "https://www.stochasticlifestyle.com/an-in-depth-look-at-vectorization/", "published_at": "2016-01-21T09:56:11+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c3252d1d6", "title": "What Exactly is Brownian Motion and Why Does it Matter?", "url": "https://www.stochasticlifestyle.com/what-exactly-is-brownian-motion/", "published_at": "2016-01-19T18:35:46+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c3338dded", "title": "Quick Optimizations in Julia for Performance: A Practical Example", "url": "https://www.stochasticlifestyle.com/optimizing-julia-performance-practical-example/", "published_at": "2016-01-19T09:18:50+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c3368ce08", "title": "Julia iFEM1: Porting Mesh Generation", "url": "https://www.stochasticlifestyle.com/julia-ifem-1-mesh-generation-and-julias-type-system/", "published_at": "2016-01-19T07:49:46+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c342c2518", "title": "WordPress Julia Syntax Highlighting", "url": "https://www.stochasticlifestyle.com/wordpress-julia-syntax-highlighting/", "published_at": "2016-01-19T02:27:45+00:00" }, { "id": "01a0d2e8-9857-7349-b2bf-bd4c34b969b3", "title": "The New Project", "url": "https://www.stochasticlifestyle.com/the-new-project/", "published_at": "2016-01-19T00:53:10+00:00" } ] posts Claim your blog
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2026

What Agentic AI “Vibe Coding” In The Hands Of Actual Programmers / Engineersoriginal ↗
12 Feb 2026
Why Julia’s GPU Accelerated ODE Solvers are 20x-100x Faster than Jax and PyTorchoriginal ↗
11 Jan 2026

2025

Claude Code sucks but is still useful: experiences maintaining Julia’s SciML scientific computing infrastructureoriginal ↗
6 Oct 2025
Implicit ODE Solvers Are Not Universally More Robust than Explicit ODE Solvers, Or Why No ODE Solver is Bestoriginal ↗
4 Sept 2025
A Guide to Gen AI / LLM Vibecoding for Expert Programmersoriginal ↗
22 Aug 2025
Machine learning with hard constraints: Neural Differential-Algebraic Equations (DAEs) as a general formalismoriginal ↗
3 Jun 2025
How chaotic is chaos? How some AI for Science / SciML papers are overstating accuracy claimsoriginal ↗
26 May 2025
A Hands on Introduction to Applied Scientific Machine Learning / Physics-Informed Learningoriginal ↗
11 May 2025
Open Source Component-Based Modeling with ModelingToolkitoriginal ↗
5 May 2025
The Numerical Analysis of Differentiable Simulation: Automatic Differentiation Can Be Incorrectoriginal ↗
20 Apr 2025
JuliaSim: Building a Product which improves Open Source Sustainabilityoriginal ↗
26 Jan 2025

2024

Differences Between Methods for Solving Stiff ODEsoriginal ↗
6 Apr 2024
Symbolic-Numerics: how compiler smarts can help improve the performance of numerical methods (nonlinear solvers in Julia)original ↗
13 Feb 2024
Semantic Versioning (Semver) is flawed, and Downgrade CI is required to fix itoriginal ↗
11 Feb 2024

2023

ChatGPT performs better on Julia than Python (and R) for Large Language Model (LLM) Code Generation. Why?original ↗
19 Nov 2023
DDPS Seminar Talk: Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous modelsoriginal ↗
12 Nov 2023
Summary of Julia Plotting Packagesoriginal ↗
17 Jun 2023

2022

Integrating equation solvers with probabilistic programming through differentiable programmingoriginal ↗
24 Nov 2022
Direct Automatic Differentiation of (Differential Equation) Solvers vs Analytical Adjoints: Which is Better?original ↗
11 Oct 2022
Is Differentiable Programming Actually Necessary? Can’t you just train the neural networks separately?original ↗
4 Oct 2022
Accurate and Efficient Physics-Informed Learning Through Differentiable Simulation (ASA Seminar Talk)original ↗
14 Jul 2022
Keynote: New Horizons in Modeling and Simulation with Julia (Modelica Conference 2021)original ↗
25 Jun 2022
Composing Modeling and Simulation with Julia (2021 Modelica Conference)original ↗
8 Apr 2022

2021

Engineering Trade-Offs in Automatic Differentiation: from TensorFlow and PyTorch to Jax and Juliaoriginal ↗
25 Dec 2021
Improved ForwardDiff.jl Stacktraces With Package Tagsoriginal ↗
19 Dec 2021
The Use and Practice of Scientific Machine Learningoriginal ↗
18 Nov 2021
When does the mean and variance define an SDE?original ↗
1 Nov 2021
Learning Epidemic Models That Extrapolate, AI4Pandemicsoriginal ↗
25 Jul 2021
Useful Algorithms That Are Not Optimized By Jax, PyTorch, or Tensorfloworiginal ↗
21 Jul 2021
ModelingToolkit, Modelica, and Modia: The Composable Modeling Future in Juliaoriginal ↗
19 Apr 2021
Generalizing Automatic Differentiation to Automatic Sparsity, Uncertainty, Stability, and Parallelismoriginal ↗
10 Mar 2021
JuliaCall Update: Automated Julia Installation for R Packagesoriginal ↗
18 Jan 2021

2020

GPU-Accelerated ODE Solving in R with Julia, the Language of Librariesoriginal ↗
24 Aug 2020
COVID-19 Epidemic Mitigation via Scientific Machine Learning (SciML)original ↗
7 Jul 2020
Cheap But Effective: Instituting Effective Pandemic Policies Without Knowing Who’s Infectedoriginal ↗
2 Jul 2020
Glue AD for Full Language Differentiable Programmingoriginal ↗
15 Jun 2020
Generalized Physics-Informed Learning through Language-Wide Differentiable Programming (Video)original ↗
31 Mar 2020
Universal Differential Equations for Scientific Machine Learning (Video)original ↗
6 Mar 2020
Scientific Machine Learning: Interpretable Neural Networks That Accurately Extrapolate From Small Dataoriginal ↗
14 Jan 2020

2019

How Inexact Models and Scientific Machine Learning Can Guide Decision Making in Quantitative Systems Pharmacologyoriginal ↗
15 Dec 2019
Recent advancements in differential equation solver softwareoriginal ↗
16 Oct 2019
A Collection of Jacobian Sparsity Acceleration Tools for Juliaoriginal ↗
6 Oct 2019
Developing Julia Packagesoriginal ↗
4 Oct 2019
When do micro-optimizations matter in scientific computing?original ↗
3 Sept 2019
The Essential Tools of Scientific Machine Learning (Scientific ML)original ↗
20 Aug 2019
Scientific AI: Domain Models with Integrated Machine Learningoriginal ↗
25 Jul 2019
Neural Jump SDEs (Jump Diffusions) and Neural PDEsoriginal ↗
5 Jun 2019

2018

Zero-Cost Abstractions in Julia: Indexing Vectors by Name with LabelledArraysoriginal ↗
12 Nov 2018
The Nonlinear Effect of Code Speed on Productivityoriginal ↗
29 Oct 2018
Some State of the Art Packages in Julia v1.0original ↗
27 Aug 2018
PuMaS.jl: Pharmaceutical Modeling and Simulation Engineoriginal ↗
13 Aug 2018
Solving Partial Differential Equations with Juliaoriginal ↗
8 Aug 2018
Why Numba and Cython are not substitutes for Juliaoriginal ↗
6 Aug 2018
DifferentialEquations.jl’s Confederated Modular APIoriginal ↗
18 Jul 2018
Simulation and Control of Biological Stochasticityoriginal ↗
5 Jun 2018
Intro to solving differential equations in Juliaoriginal ↗
5 Mar 2018
Using Juno for Interactive Test-Driven Julia Package Developmentoriginal ↗
19 Feb 2018
Algorithm efficiency comes from problem informationoriginal ↗
4 Jan 2018

2017

Solving Systems of Stochastic PDEs and using GPUs in Juliaoriginal ↗
11 Dec 2017
Some tips for your Google Summer of Code Applicationoriginal ↗
13 Nov 2017
DifferentialEquations.jl 3.0 and a Roadmap for 4.0original ↗
30 Oct 2017
I Like Julia Because It Scales and Is Productive: Some Insights From A Julia Developeroriginal ↗
13 Oct 2017
A Comparison Between Differential Equation Solver Suites In MATLAB, R, Julia, Python, C, Mathematica, Maple, and Fortranoriginal ↗
26 Sept 2017
Video Introduction to DifferentialEquations.jloriginal ↗
7 Jul 2017
Type-Dispatch Design: Post Object-Oriented Programming for Juliaoriginal ↗
29 May 2017
Video Blog: Developing and Editing Julia Packagesoriginal ↗
16 May 2017
DifferentialEquations.jl 2.0: State of the Ecosystemoriginal ↗
8 May 2017
Some Fun With Julia Types: Symbolic Expressions in the ODE Solveroriginal ↗
4 May 2017
Building a Web App in Julia: DifferentialEquations.jl Onlineoriginal ↗
17 Jan 2017

2016

6 Months of DifferentialEquations.jl: Where We Are and Where We Are Goingoriginal ↗
15 Dec 2016
Modular Algorithms for Scientific Computing in Juliaoriginal ↗
7 Dec 2016
7 Julia Gotchas and How to Handle Themoriginal ↗
4 Oct 2016
Introducing DifferentialEquations.jloriginal ↗
1 Aug 2016
Using Julia’s Type System For Hidden Performance Gainsoriginal ↗
7 Jun 2016
Finalizing Your Julia Package: Documentation, Testing, Coverage, and Publishingoriginal ↗
16 May 2016
Optimal Number of Workers for Parallel Juliaoriginal ↗
16 Apr 2016
Holding off on Julia for a little bit… you should blog!original ↗
28 Mar 2016
Benchmarks of Multidimensional Stack Implementations in Juliaoriginal ↗
20 Mar 2016
MATLAB 2016a Release Summary for Scientific Computingoriginal ↗
15 Mar 2016
Interfacing with a Xeon Phi via Juliaoriginal ↗
4 Mar 2016
Multiple-GPU Parallelism on the HPC with Juliaoriginal ↗
28 Feb 2016
Tutorial for Julia on the HPC with GPUsoriginal ↗
23 Feb 2016
Multi-node Parallelism in Julia on an HPC (XSEDE Comet)original ↗
23 Feb 2016
Blog Upgraded: A Good Experience With Bluehostoriginal ↗
23 Feb 2016
Comparison of US HPC Resourcesoriginal ↗
20 Feb 2016
Using Julia’s C Interface to Utilize C Librariesoriginal ↗
4 Feb 2016
Setting Variables Element-wise in a Matrix in Mathematicaoriginal ↗
2 Feb 2016
Simple Parallel Optimization in Mathematicaoriginal ↗
2 Feb 2016
Why is Mathematica Stopping My Long Calculation?original ↗
30 Jan 2016
Julia iFEM3: Solving the Poisson Equation via MATLAB Interfacingoriginal ↗
24 Jan 2016
Julia iFEM 2: Optimizing Stiffness Matrix Assemblyoriginal ↗
23 Jan 2016
Optimizing .*: Details of Vectorization and Metaprogrammingoriginal ↗
21 Jan 2016
What Exactly is Brownian Motion and Why Does it Matter?original ↗
19 Jan 2016
Quick Optimizations in Julia for Performance: A Practical Exampleoriginal ↗
19 Jan 2016
Julia iFEM1: Porting Mesh Generationoriginal ↗
19 Jan 2016
WordPress Julia Syntax Highlightingoriginal ↗
19 Jan 2016
The New Projectoriginal ↗
19 Jan 2016