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1.
▲
Autodiff: Simple C++17 library for Automatic Differentiation
(github.com/autodiff)
3 points
ubj
4 years ago
discuss
2.
▲
Autodiff Puzzles: puzzles for learning about derivatives in tensor libraries
(github.com/srush)
2 points
sebg
2 years ago
discuss
3.
▲
Autodiff Puzzles
(github.com/srush)
2 points
sva_
4 years ago
discuss
4.
▲
Puzzles for Automatic Differentiation
(github.com/srush)
1 point
haltist
3 years ago
discuss
5.
▲
Show HN: I wrote a (slightly less slow, but still bad) autodiff from scratch
(github.com/mebassett)
1 point
mebassett
8 months ago
discuss
6.
▲
Show HN: Backwards automatic differentiation in ~100 lines of Python
(github.com/AirFig)
2 points
AirFig
4 years ago
discuss
7.
▲
Show HN: Autogenerate efficient backward kernels for Triton
(github.com/IaroslavElistratov)
1 point
iaroo
7 months ago
discuss
8.
▲
Tiny-autodiff: A tiny autograd library made for educational purposes in D
(github.com/rillki)
1 point
teleforce
2 years ago
discuss
9.
▲
Micrograd-CUDA: adapting Karpathy's tiny autodiff engine for GPU acceleration
(github.com/mlecauchois)
178 points
cataPhil
2 years ago
13 comments
10.
▲
Show HN: Tesseract Core – Autodiff-native, self-documenting software components
(github.com/pasteurlabs)
15 points
dionhaefner
a year ago
discuss
11.
▲
Show HN: Minimal DL library in C – 24 NAIVE CUDA/CPU ops, autodiff, Python API
(github.com/IaroslavElistratov)
13 points
iaroo
6 months ago
1 comment
12.
▲
Show HN: KANN – mid-scale deep learning and autodiff in ANSI C (4 files; 4k LOC)
(github.com/attractivechaos)
5 points
attractivechaos
8 years ago
3 comments
13.
▲
Show HN: Efficient autodiff using codual numbers
(github.com/wlad-svennik)
3 points
ogogmad
4 years ago
discuss
14.
▲
Micrograd a 24kb pure Python autodiff lib
(github.com/brief-ds)
2 points
aglassofred
a year ago
1 comment
15.
▲
Catalyst: Autodifferentiation using Enzyme and LLVM with a Python/Jax front end
(github.com/PennyLaneAI)
1 point
infinitewalk
2 years ago
discuss
16.
▲
Show HN: Boldly go where Gradient Descent has never gone before with DiscoGrad
(github.com/DiscoGrad)
232 points
frankling_
2 years ago
66 comments
17.
▲
Show HN: I built a deep learning engine from scratch in Python
(github.com/whitegra)
30 points
gmwhitebox_dev
a year ago
3 comments
18.
▲
Show HN: Self-growing neural networks via a custom Rust-to-LLVM compiler
(github.com/pierridotite)
8 points
pierridotite
5 months ago
3 comments
19.
▲
Show HN: I wrote my first neural network
(github.com/stupid-genius)
6 points
allenng
3 months ago
discuss
20.
▲
Show HN: L-Rep:Geometry engine,GA multivectors,dynamic trees in a single integer
(github.com/nahhididwin)
3 points
InputNothing
3 months ago
discuss
21.
▲
Show HN: DiscoGrad – Automatically differentiate across branches in C++ programs
(github.com/DiscoGrad)
2 points
frankling_
2 years ago
discuss
22.
▲
Show HN: Equinox (1.3k stars), a JAX library for neural networks and sciML
(github.com/patrick-kidger)
1 point
patrickkidger
3 years ago
discuss
23.
▲
Show HN: Llama-8B Teaches Itself Baby Steps to Deep Research Using RL
(github.com/dCaples)
39 points
diegocaples
a year ago
3 comments
24.
▲
Show HN: Autodistill – Use big slow foundation models to train small fast models
(github.com/autodistill)
18 points
yeldarb
3 years ago
discuss
25.
▲
Show HN: Autodidact – Self-evolving local-first AI agent
(github.com/BuffaloTechRider)
8 points
waterbuffaloai
18 days ago
4 comments
26.
▲
Show HN: Autodistill, automated image labeling with foundation vision models
(github.com/autodistill)
4 points
zerojames
3 years ago
discuss
27.
▲
Autodistill: Use foundation vision models to train smaller, supervised models
(github.com/autodistill)
4 points
zerojames
3 years ago
discuss
28.
▲
Autodiscover-modules: Auto discovery modules in Node.js
(github.com/francocorreasosa)
1 point
francocorrea
9 years ago
discuss
29.
▲
AutoRIFT: A Python module for finding the pixel displacement between two images
(github.com/nasa-jpl)
22 points
wh313
4 years ago
5 comments
30.
▲
Generative AI Email Assistant
(github.com/jacob-dietle)
1 point
todsacerdoti
3 years ago
discuss
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