tcfkaj Goto Github PK

6358-project

Class project for Linear Models

agents

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

based.cooking

A simple culinary website.

candy-cane

RNN-LTSM to predict deferment on synthetic oil-well data.

ccv

C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library

clip-ods

CLIP Object Detection, search object on image using natural language #Zeroshot #Unsupervised #CLIP #ODS

cog-stable-diffusion-nsfw

Diffusers Stable Diffusion as a Cog model

coq_nvim

Fast as FUCK nvim completion. SQLite, concurrent scheduler, hundreds of hours of optimization.

cuda-aarch64-cc-mxnet-opencv

deviation-network-image

Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.

dwm

Luke's build of dwm

dwmblocks

My status bar: my build of the modular dwmblocks

gluon-cv

Gluon CV Toolkit

jessturnerphoto.com

A simple static site generator for photoessays

kernel-based-regression

Non-linear regression with kernel-based regularization.

larbs

Luke's Auto-Rice Bootstrapping Scripts: Installation Scripts for My Arch Linux Meta-Distribution

mutt-wizard

A system for automatically configuring mutt and isync with a simple interface and safe passwords

null-ls.nvim

Use Neovim as a language server to inject LSP diagnostics, code actions, and more via Lua.

pydegensac

Advanced RANSAC (DEGENSAC) with bells and whistles for H and F estimation

pytorch_geometric

Graph Neural Network Library for PyTorch

r-stock-clustering

clustering stock time-series.

rustlings

:crab: Small exercises to get you used to reading and writing Rust code!

st

Luke's fork of the suckless simple terminal (st) with vim bindings and Xresource compatibility.

voidrice

My dotfiles (deployed by LARBS)

xgboost-survival-embeddings

Improving XGBoost survival analysis with embeddings and debiased estimators