Stars
Building a quick conversation-based search demo with Lepton AI.
NASRec Weight Sharing Neural Architecture Search for Recommender Systems
A Pythonic framework to simplify AI service building
An implementation of a deep learning recommendation model (DLRM)
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Benchmark datasets, data loaders, and evaluators for graph machine learning
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures
Graph Neural Network Library for PyTorch
Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib).
Implementation of Graph Convolutional Networks in TensorFlow
TensorFlow Code for paper "Efficient Neural Architecture Search via Parameter Sharing"
NASBench: A Neural Architecture Search Dataset and Benchmark
Code for visualizing the loss landscape of neural nets
Count the MACs / FLOPs of your PyTorch model.
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
The most cited deep learning papers
CondenseNet: Light weighted CNN for mobile devices
A PyTorch Implementation of ConvDeltaOrthogonal Initializer
Differentiable architecture search for convolutional and recurrent networks
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"
Efficient GPU kernels for block-sparse matrix multiplication and convolution