Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Core deep-learning frameworks and libraries for pretraining and distributed training.
Signals: deep-learning, neural-network, pytorch, tensorflow, jax, distributed-training, training, deepspeed
2,663 results
Tensorflow implementation of Product-based Neural Networks. An extended version is at https://github.com/Atomu2014/product-nets-distributed.
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
Live-bending a foundation model’s output at neural network level.
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
[NeurIPS 2024] Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR
PyTorch implementation of Non-Local Neural Networks (https://arxiv.org/pdf/1711.07971.pdf)
Estimate/count FLOPS for a given neural network using pytorch
CORAL and CORN implementations for ordinal regression with deep neural networks.
Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"
Code for paper "Synthesizing the preferred inputs for neurons in neural networks via deep generator networks"
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist)
Enabling easy statistical significance testing for deep neural networks.
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."
Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.
Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"
Neural Network Tools: Converter and Analyzer. For caffe, pytorch, draknet and so on.
The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks
OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms
The Prodigy optimizer and its variants for training neural networks.
DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
24,545 repositories in the index in total.
