yangerkun

Adversarial-examples-for-hamming-space-search

Code for Adversarial examples for hamming space search

Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

Classification-with-noisy-labels-by-importance-reweighting

TPAMI: Classification with noisy labels by importance reweighting.

DCGAN-tensorflow

A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

Deep-Learning-Papers-Reading-Roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

DeepHashingBaselines

Deep Hashing Baselines

DefenseByAttack

Code for paper "One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples." (https://arxiv.org/abs/1911.11219)

IJCAI2018_SSDH

Semantic Structure-based Unsupervised Deep Hashing IJCAI2018

MomentumContrast.pytorch

Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning

yangerkun/IJCAI2018_SSDH

Semantic Structure-based Unsupervised Deep Hashing IJCAI2018

yangerkun/Adversarial-examples-for-hamming-space-search

Code for Adversarial examples for hamming space search

yangerkun/Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

yangerkun/Classification-with-noisy-labels-by-importance-reweighting

TPAMI: Classification with noisy labels by importance reweighting.

yangerkun/DefenseByAttack

Code for paper "One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples." (https://arxiv.org/abs/1911.11219)

yangerkun/MomentumContrast.pytorch

Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning

yangerkun/Mutual-Quantization-for-Cross-Modal-Search-With-Noisy-Labels

yangerkun/SML-Group

The code that sml group often uses

yangerkun/vimrc

The ultimate Vim configuration: vimrc

yangerkun/AD_Prediction

Alzheimer's Disease Prediction by using ResNet, AlexNet

yangerkun/Advances-in-Label-Noise-Learning

A curated (most recent) list of resources for Learning with Noisy Labels

yangerkun/BrainPrep

Preprocessing pipeline on Brain MR Images through FSL and ANTs, including registration, skull-stripping, bias field correction, enhancement and segmentation.

yangerkun/CSrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

yangerkun/fast_adversarial

[ICLR 2020] A repository for extremely fast adversarial training using FGSM

yangerkun/FINE_official

NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"

yangerkun/HashNet

Code release for "HashNet: Deep Learning to Hash by Continuation" (ICCV 2017)

yangerkun/HFCN_TPAMI

yangerkun/imgaug

Image augmentation for machine learning experiments.

yangerkun/kWTA-Activation

yangerkun/LC-Booster

yangerkun/LungCancerDetection

Use CNN to detect nodules in LIDC dataset.

yangerkun/M3d-Cam

yangerkun/PlotNeuralNet

Latex code for making neural networks diagrams

yangerkun/pytorch-metric-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

yangerkun/SEARLE

[ICCV 2023] - Zero-shot Composed Image Retrieval with Textual Inversion

yangerkun/T-Revision

NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?

yangerkun/tensorflow-triplet-loss

Implementation of triplet loss in TensorFlow

yangerkun/TikZ

Complete collection of my PGF/TikZ figures.

yangerkun/Two-Stream-Deep-Hashing-With-Class-Specific-Centers-for-Supervised-Image-Search

yangerkun/yangerkun.github.io

Stylish, minimalistic theme for jekyll.