lilujunai Goto Github PK

revisiting_saliency

There and Back Again: Revisiting Backpropagation Saliency Methods (CVPR 2020)

rewinding-iclr20-public

rexnet

Official Pytorch implementation of ReXNet (Rank eXpansion Network) with pretrained models

rezero

Official PyTorch Repo for "ReZero is All You Need: Fast Convergence at Large Depth"

rfdn

Residual Feature Distillation Network for Lightweight Image Super-Resolution

rfs

rl-starter-files

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code

rl-stock

📈 如何用深度强化学习自动炒股

robust-f-divergence-measures

robustdarts

Understanding and Robustifying DARTS

robustness

Corruption and Perturbation Robustness (ICLR 2019)

robustness-aware-pruning-admm

Code release for "Adversarial Robustness vs Model Compression, or Both?"

rocket-launching

A universal and efficient framework for training well-performing light net

role-kd

Role-Wise Data Augmentation for Knowledge Distillation

rotograd

Official Pytorch's implementation of RotoGrad

runx

Deep Learning Experiment Management

s2sd

Implementation for S2SD - Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

s3nas

Fast NPU-aware Neural Architecture Search

sacred

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

saliencymix

SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

sam

Code for the CVPR paper "SAM: The Sensitivity of Attribution Methods to Hyperparameters"

san

Exploring Self-attention for Image Recognition, CVPR2020.

sanas

Stochastic Adaptive Neural Architecture Search

sandwich-batch-normalization

[preprint] "Sandwich Batch Normalization" Xinyu Gong, Wuyang Chen, Tianlong Chen and Zhangyang Wang

scale-adjusted-training

PyTorch implementation of Towards Efficient Training for Neural Network Quantization

scale-invariant-cnns

Study the Scale Invariance or Equivariance Convolutional Neural Network

scienceplots

Matplotlib styles for scientific plotting

scope

Making deep learning measurements involving the gradient and the Hessian

scot

sd-bnn

Self-Distribution BNN