Pinned Repositories
deep_Mahalanobis_detector
Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".
interpretability-by-parts
Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)
libsvm
LIBSVM -- A Library for Support Vector Machines (unofficial snapshot dist mirror)
MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
matching-networks-pytorch
Matching Networks for one shot learning
medical-imaging-datasets
A list of Medical imaging datasets.
Prototypical-Networks-for-Few-shot-Learning-PyTorch
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
pytorch-center-loss
Pytorch implementation of Center Loss
PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
SPH6004
Assignment1
WANG1102's Repositories
WANG1102/SPH6004
Assignment1
WANG1102/deep_Mahalanobis_detector
Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".
WANG1102/interpretability-by-parts
Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)
WANG1102/libsvm
LIBSVM -- A Library for Support Vector Machines (unofficial snapshot dist mirror)
WANG1102/MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
WANG1102/matching-networks-pytorch
Matching Networks for one shot learning
WANG1102/medical-imaging-datasets
A list of Medical imaging datasets.
WANG1102/Prototypical-Networks-for-Few-shot-Learning-PyTorch
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
WANG1102/pytorch-center-loss
Pytorch implementation of Center Loss
WANG1102/PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
WANG1102/SOD-CNNs-based-code-summary-
The summary of code and paper for salient object detection with deep learning
WANG1102/Stain_Normalization
Some stain normalization code