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Section: Specialized Frameworks · Graph neural network library for PyTorch enabling molecular modeling, materials discovery, protein interaction networks, and scientific knowledge graph learning (23.7k+ stars)
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Graph neural network library for PyTorch enabling molecular modeling, materials discovery, protein interaction networks, and scientific knowledge graph learning (23.7k+ stars)
Section: Specialized Frameworks · Graph neural network library for PyTorch enabling molecular modeling, materials discovery, protein interaction networks, and scientific knowledge graph learning (23.7k+ stars)
Section: Tools · Geometric deep learning extension library for PyTorch.
Section: Deep Learning Packages
Section: Python · > Graph Neural Network Library for PyTorch.
Section: 1. Core Frameworks & Libraries · Library for deep learning on irregular input data such as graphs, point clouds, and manifolds. Part of the PyTorch ecosystem.
Section: Computation and Communication Optimisation · PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Section: Other · Graph Neural Network Library for PyTorch
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.
(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
Visualizer for deep learning and machine learning models (no Python code, but visualizes models from most Python Deep Learning frameworks).
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow. [Apache2]
Official TensorFlow repository of state-of-the-art (SOTA) models and modeling solutions. Contains reference implementations for BERT, ResNet, Transformer, and many more with pre-trained weights and training scripts. Apache 2.0 licensed.
Modern, comprehensive probabilistic programming framework in Python. Bayesian modeling with advanced MCMC sampling, variational inference, and seamless integration with ArviZ for visualization. Apache 2.0 licensed.
Scikit-learn is a powerful machine learning library that provides a wide variety of modules for data access, data preparation and statistical model building.