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ChrisRackauckas

3,832 karma · joined October 6, 2016

I am the developer of the SciML Scientific Machine Learning Open Source Software Organization (https://sciml.ai/), an organization for Julia, Python and R packages for integrated, composible, and fast scientific machine learning. I also have used quite a bit of MATLAB, C, and Fortran (well, at least used for numerical work), but these days. I think the purpose of discussing technical topics is the dissemination of ideas, so let's bring each other up not down!
submissionscomments

GPT-5.6 vs. Claude Fable 5 for Physical AI, which performs best?

juliahub.com·1 pts·ChrisRackauckas·
0

Dyad 2.0: What Agentic AI Means for the Future of Computer Languages

juliahub.com·3 pts·ChrisRackauckas·
0

Agentic AI for Model-Based Engineering: How Dyad Ensures Correctness

juliahub.com·3 pts·ChrisRackauckas·
0

Why No Ode Solver Is Best

stochasticlifestyle.com·2 pts·ChrisRackauckas·
0

A guide to Gen AI / LLM vibecoding for expert programmers

stochasticlifestyle.com·128 pts·ChrisRackauckas·
117

Why Dyad?: A Perspective for Modelica Users

juliahub.com·3 pts·ChrisRackauckas·
0

Dyad: Making Hardware as Easy as Software

juliahub.com·3 pts·ChrisRackauckas·
1

HuggingFace deprecates TensorFlow and Jax support

twitter.com·5 pts·ChrisRackauckas·
0

Machine learning with hard constraints: Neural Differential-Algebraic Equations

stochasticlifestyle.com·2 pts·ChrisRackauckas·
0

How chaotic is chaos? How some AI for Science / SciML overstates accuracy claims

stochasticlifestyle.com·4 pts·ChrisRackauckas·
0

Compilation of Julia code for deployment in model-based engineering

arxiv.org·4 pts·ChrisRackauckas·
0

Julia Developer Experience with Tim Holy – Julia Dispatch Podcast [video]

youtube.com·3 pts·ChrisRackauckas·
0

Static Compilation of Julia with Jeff Bezanson – Julia Dispatch Podcast [video]

youtube.com·7 pts·ChrisRackauckas·
0

Add –trim option for generating smaller binaries

jbytecode.github.io·3 pts·ChrisRackauckas·
0

Semantic Versioning (Semver) is flawed, and Downgrade CI is required to fix it

stochasticlifestyle.com·4 pts·ChrisRackauckas·
1

Julia SciML Lorenz equation solver staically compiled to WebAssembly

tshort.github.io·3 pts·ChrisRackauckas·
3

Julia will cache precompiled binaries of packages v1.9

twitter.com·4 pts·ChrisRackauckas·
0

Show HN: Differentiable Programming on Discrete Stochastic Programs

twitter.com·2 pts·ChrisRackauckas·
0

Automatic Differentiation of Solvers vs. Analytical Adjoints: Which Is Better?

stochasticlifestyle.com·2 pts·ChrisRackauckas·
0

Julia SciML Ecosystem Update: Better Error Messages, Compile Times, and Docs

sciml.ai·3 pts·ChrisRackauckas·
0

Is Differentiable Programming Necessary?

stochasticlifestyle.com·3 pts·ChrisRackauckas·
0

Julia Back-End for LFortran (LFortran – Julia Transpilation)

discourse.julialang.org·55 pts·ChrisRackauckas·
4

How Julia ODE Solve Compile Time Was Reduced from 30 Seconds to 0.1

sciml.ai·177 pts·ChrisRackauckas·
16

Julia for Epidemiology

medium.com·5 pts·ChrisRackauckas·
0

Symbolic-Numeric Integration of Univariate Expressions via Sparse Regression

arxiv.org·12 pts·ChrisRackauckas·
6

Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia

stochasticlifestyle.com·234 pts·ChrisRackauckas·
73

Using machine learning to derive black hole motion from gravitational waves

phys.org·2 pts·ChrisRackauckas·
0

Implications of Delayed Reopening in Controlling the Covid-19 Surge in USA

spj.sciencemag.org·3 pts·ChrisRackauckas·
2

Composability in Julia: Implementing Deep Equilibrium Models via Neural ODEs

julialang.org·117 pts·ChrisRackauckas·
48

Abstractdifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia

arxiv.org·2 pts·ChrisRackauckas·
2
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