EMP325

ANL

Code for "Adversarial Noise Layer: Regularize Neural Network By Adding Noise"

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

GAM

The official repo for CVPR2023 highlight paper "Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization".

WSAM

WSAM

SAM-ON

tied-augment

Tied-Augment: Controlling Representation Similarity Improves Data Augmentation

PyHessian

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

SAF

O2U-Net

paper "O2U-Net: A Simple Noisy Label Detection Approach for Deep Neural Networks" code

YOLOv4-pytorch

This is a pytorch repository of YOLOv4, attentive YOLOv4 and mobilenet YOLOv4 with PASCAL VOC and COCO

TWA

Trainable Weight Averaging for Fast Convergence and Better Generalization

RMSGD

Exploiting Explainable Metrics for Augmented SGD [CVPR2022]

R-Drop

GSAM

PyTorch repository for ICLR 2022 paper (GSAM) which improves generalization (e.g. +3.8% top-1 accuracy on ImageNet with ViT-B/32)

DLTH

LPF-SGD

sam

SAM: Sharpness-Aware Minimization (PyTorch)

Efficient_SAM

PAC-Bayes-IB

Official repo for PAC-Bayes Information Bottleneck.

deeplearningtheory

TRADES

TRADES (TRadeoff-inspired Adversarial DEfense via Surrogate-loss minimization)

awesome-latex-cv

Latex CV template built with Font Awesome.

ASAM

Implementation of ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks, ICML 2021.

AdversaryLossLandscape

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Adabelief-Optimizer

Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

AMP-Regularizer

Code for our paper "Regularizing Neural Networks via Adversarial Model Perturbation", CVPR2021

pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

Friendly-Adversarial-Training

Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)

uncertainty-baselines

High-quality implementations of standard and SOTA methods on a variety of tasks.