Stars
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
A curated list of awesome Machine Learning frameworks, libraries and software.
A toolkit for developing and comparing reinforcement learning algorithms.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Graph Neural Network Library for PyTorch
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
fsociety Hacking Tools Pack – A Penetration Testing Framework
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Keras code and weights files for popular deep learning models.
Implementation of Graph Convolutional Networks in TensorFlow
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Web interface for browsing, search and filtering recent arxiv submissions
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
dataset and code for 2016 paper "Learning a Driving Simulator"
Representation learning on large graphs using stochastic graph convolutions.
Entropy Based Sampling and Parallel CoT Decoding
Tensorforce: a TensorFlow library for applied reinforcement learning
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
Benchmark datasets, data loaders, and evaluators for graph machine learning