No-code GUI for Physics-Informed Neural Networks (PINNs)
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Updated
Sep 1, 2026 - Python
No-code GUI for Physics-Informed Neural Networks (PINNs)
Some summaries for lectures of the RW/CSE curriculum
Define and Run Computational Experiments on Cybershuttle
A Dynamic System Framework Engine for modelling many different physical and mathematical systems. DSFE's code is prodominantly programmed in C++/C, with the GUI using Vulkan SDK and GLSL for the graphics pipeline. Currently supports Linux (x86/64) and Windows (x86/64)
Independent scientific initiative exploring cognition, internal observers, reproducible simulations, and computational models of knowledge formation.
Interactive Streamlit application for exploring, comparing, and analyzing stochastic 3D root architecture simulations.
Open-source, local-first desktop software for building, analysing and reproducing mathematical experiments. Model Laboratory combines typed model, run and artifact protocols, canonical experiment bundles, provenance tracking, extensible scientific packs and a review-gated AI interpreter, with computation kept on the user’s machine.
A theory of identifiability, minimal causal interfaces, and measurement limits for adaptive systems.
Reproducible scientific-computing framework for stochastic 3D root architecture simulation, quantitative analysis, and scalable Monte Carlo experiments.
Curated collection of resources for computational materials science
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