evcu / numpy_autograd
a simple implementation of autograd engine
β23Updated 6 years ago
Alternatives and similar repositories for numpy_autograd:
Users that are interested in numpy_autograd are comparing it to the libraries listed below
- Toy implementations of some popular ML optimizers using Python/JAXβ44Updated 3 years ago
- A minimal implementation of autograd (in pure Python) π°β95Updated 3 years ago
- coding an autograd from scratchβ177Updated 6 years ago
- Documentation:β119Updated last year
- Rudimentary automatic differentiation frameworkβ74Updated 6 years ago
- Some small scale experiments for my blog posts πβ79Updated 2 years ago
- Worked example of the process from Python source to CUDA kernel execution with Numbaβ40Updated 7 months ago
- Code for the book "The Elements of Differentiable Programming".β83Updated last month
- A selection of neural network models ported from torchvision for JAX & Flax.β44Updated 4 years ago
- Customized matrix multiplication kernelsβ54Updated 3 years ago
- Neural Networks library in pure numpyβ67Updated last year
- Progress, Notes, Summaries and a lot of Questions on Machine Learningβ55Updated 5 years ago
- β°οΈ RockyML - A High-Performance Scientific Computing Framework for Non-smooth Machine Learning Problemsβ19Updated 2 years ago
- Codebase associated with the PyTorch compiler tutorialβ45Updated 5 years ago
- Functional machine learning for funβ84Updated 3 years ago
- Symbolic API for model creation in PyTorch.β66Updated last month
- Implementation of Machine Learning algorithms from scratch in Pythonβ34Updated 5 years ago
- Yaae: Yet another autodiff engine (written in Numpy).β27Updated last year
- A curated list of resources to help with computational research.β20Updated 2 years ago
- Blazingly fast capsule networks in 75 lines of pytorch+einopsβ26Updated 3 years ago
- Mathematical operations for JAX pytreesβ199Updated 4 months ago
- Probabilistic Programming eXecution protocol (PPX)β75Updated 3 years ago
- A web based tool for visualization of the forward and reverse modes of automatic differentiationβ17Updated 11 months ago
- Implementations and checkpoints for ResNet, Wide ResNet, ResNeXt, ResNet-D, and ResNeSt in JAX (Flax).β109Updated 2 years ago
- a mini Deep Learning framework supporting GPU accelerations written with CUDAβ32Updated 4 years ago
- Notebooks for the "JAX in Action" bookβ144Updated 10 months ago
- Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditionβ¦β173Updated this week
- β166Updated 8 months ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)β115Updated 3 years ago
- Dive into Jax, Flax, XLA and C++β31Updated 5 years ago