EthanLan

BCNN

Bayesian Convolutional Neural Networks for Compressed Sensing Restoration

deeplearning-models

A collection of various deep learning architectures, models, and tips

pytorch-cifar

95.47% on CIFAR10 with PyTorch

A-Tighter-Genearlization-Bound-in-deep-learning

Angular-Penalty-Softmax-Losses-Pytorch

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

Conference-Acceptance-Rate

Acceptance rates for the major AI conferences

D-AMP_Toolbox

This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

GCE

[ICCV'19] Improving Adversarial Robustness via Guided Complement Entropy

ImageNet-Adversarial-Training

ImageNet classifier with state-of-the-art adversarial robustness

Learning_to_diversify

lsoftmax-pytorch

The Pytorch Implementation of L-Softmax

ME-ADA

"Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).

models

Models and examples built with TensorFlow

pytorch-tiny-imagenet

pytorch-tiny-imagenet

RNAN

PyTorch code for our ICLR 2019 paper "Residual Non-local Attention Networks for Image Restoration"