FeynmanDNA

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

tqdm

:zap: A Fast, Extensible Progress Bar for Python and CLI

pytorch_geometric

Graph Neural Network Library for PyTorch

Machine-Learning-Collection

A resource for learning about Machine learning & Deep Learning

umap

Uniform Manifold Approximation and Projection

cvxpy

A Python-embedded modeling language for convex optimization problems.

biopython

Official git repository for Biopython (originally converted from CVS)

pytorch-a2c-ppo-acktr-gail

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

Hands-on-RL

https://hrl.boyuai.com/

pdf2image

A python module that wraps the pdftoppm utility to convert PDF to PIL Image object

nlp-tutorial

A list of NLP(Natural Language Processing) tutorials

control-flag

A system to flag anomalous source code expressions by learning typical expressions from training data

CLR

EfficientZero

Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.

SGDR

numerical-veliz

Numerical Analysis code from the Oscar Veliz YouTube Channel

Convolutional-Prototype-Learning

An implementation (TensorFlow) of CPL and GCPL appeared in CVPR2018 paper: "Robust Classification with Convolutional Prototype Learning"

VesselGraph

graph_datasets

Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.

TD3-Bittle

Benchmarking TD3 and DDPG on PyBullet

vessap

Experimental code and examples for: Automated analysis of whole brain vasculature using machine learning

networkx-guide

We here are very big fans of NetworkX as a graph library and its comprehensive set of graph algorithms. For many though, working with NetworkX involves a steep learning curve. This guide is designed as an aid for beginners and experienced users to find specific tips and explore the world of complex networks.

SummerCourse2021

ml-cookbook

Machine learning notebooks and code used for demonstration purposes

introduction-to-epidemics

An introduction to epidemic modelling in its various guises

you-me-and-uaf

Use-After-Free Examples

Rknots

An R package for the topological analysis of knotted 3D structures (with a focus on biological polymers)

SpineAI-Bilsky-Grading

Computer-Simulation-of-Protein-Folding-using-the-3D-HP-Lattice-Model

Molecular_Dynamics

Simulated annealing and replica exchange implementation in Python and using NumPy library