Austin Huang's repositories
awesome-haskell-deep-learning
In the tradition of "awesome" (curated) lists, this is a list of references and code for doing deep learning in Haskell.
pytorch-sqlite
Example using sqlite with a Pytorch Dataset Interface
hello-monad
Trivial (~30 LOC) "hello world" examples of commonly used monad classes.
annotated-transformer
http://nlp.seas.harvard.edu/2018/04/03/attention.html
state-logger
Trivially minimal state log for python, primarily for machine learning experimentation
deep-review
A collaboratively written review paper on deep learning, genomics, and precision medicine
examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
haskell-servant-cookbook
Haskell Servant Cookbook
MiDaS
Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
minitorch-js
Minitorch in javascript
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
shaders
Circle C++ shaders
summer-of-haskell
Source code of summer.haskell.org
wgpu-native
Native WebGPU implementation based on wgpu-core
whisper.cpp
Port of OpenAI's Whisper model in C/C++
yew
Rust / Wasm framework for building client web apps