Stars
Implementation of the paper Parameter-Efficient Transfer Learning for NLP, Houlsby [Google], 2019. Published in ICML 2019.
Paper Implementation for "Parameter-Efficient Transfer Learning for NLP"
Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)
Differentiable architecture search for convolutional and recurrent networks
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Fast and flexible AutoML with learning guarantees.
Implementation of ' Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles'
SPOS(Single Path One-Shot Neural Architecture Search with Uniform Sampling) rebuilt in Pytorch with single GPU.
Codes for our paper "Progressive Differentiable Architecture Search:Bridging the Depth Gap between Search and Evaluation"
Automated neural architecture search algorithms implemented in PyTorch and Autogluon toolkit.
Pytorch Implementation of Neural Architecture Optimization
PyTorch port of "Efficient Neural Architecture Search via Parameters Sharing"
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"