remunds

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

supabase

The open source Firebase alternative. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

StableLM

StableLM: Stability AI Language Models

Open3D

Open3D: A Modern Library for 3D Data Processing

petals

🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

pyro

Deep universal probabilistic programming with Python and PyTorch

nhost

The Open Source Firebase Alternative with GraphQL.

OpenPCDet

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

envd

🏕️ Reproducible development environment

Open3D-ML

An extension of Open3D to address 3D Machine Learning tasks

uncertainty-baselines

High-quality implementations of standard and SOTA methods on a variety of tasks.

lovely-tensors

Tensors, for human consumption

blitz-bayesian-deep-learning

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

edward2

A simple probabilistic programming language.

calibration-framework

The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a neural network.

SPFlow

Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks

dl-with-bayes

Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"

probai-2022

Materials of the Nordic Probabilistic AI School 2022.

probflow

A Python package for building Bayesian models with TensorFlow or PyTorch

TyXe

conformal_training

This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classifiers".

PointPillars

My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-Vision

Pytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple version)

uncertainty-wizard

Uncertainty-Wizard is a plugin on top of tensorflow.keras, allowing to easily and efficiently create uncertainty-aware deep neural networks. Also useful if you want to train multiple small models in parallel.

aiosteampy

Trade and interact with steam market, webapi, guard.

pytorch-mlflow-optuna

Tutorial on training a PyTorch neural network model using MLflow for experiment tracking & Optuna for hyperparameter optimization.

simple-einet

An implementation of EinsumNetworks in PyTorch.

bayesian-torch

An easy-to-use framework to turn any neural network definition in PyTorch into a Bayesian neural network.