I wrote an autodiff in C++ and implemented LeNet with it
In plain words
This project is an automatic differentiation library written in C++ with a LeNet neural network implementation demonstrating its capabilities. It is designed for developers interested in understanding how autodiff systems work and how to build neural networks from scratch. The implementation shows practical application of gradient computation, making it useful for educational purposes or as a foundation for machine learning experimentation in C++.
written from the facts on this page · September 2026
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Life & fun · 26d ago · everycube.alen.is
Hi HN, I built Eigendrum, a web tool that solves the 2D wave equation for arbitrary shapes so you can hear what they sound like as drums. How it works: * Solves -∇²u = λu using finite element analysis (Kφ = λMφ) on a triangle mesh. * Validated to <0.1% error against closed-form solutions for circles (Bessel zeros) and rectangles. * Sound model factors in strike location, Rayleigh damping, and mallet width. * Includes Kac drums I & II to demonstrate identical sound spectra from different geometries. * No frameworks, build steps, or dependencies. Repo and tests:…
Life & fun · 27d ago · baselashraf81.github.io
Launched alongside, October 2024
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Softr for Notion▲925Turn Notion databases into portals & apps with no code
Dev tools · 2024 · softr.io
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Work · 2024 · generalcollaboration.com