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Prototypical-Networks-for-Few-shot-Learning-PyTorch

Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch

Market-1501_Attribute

27 hand-annotated attributes of Market-1501

cnn_graph

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Towards-A-Deep-and-Unified-Understanding-of-Deep-Neural-Models-in-NLP

Code implementation of paper Towards A Deep and Unified Understanding of Deep Neural Models in NLP

SAGE

A tensorflow implementation of self attentive graph embedding (SAGE) in WWW 2019

euler

A distributed graph deep learning framework.

GraphSAGE

Representation learning on large graphs using stochastic graph convolutions.

pytorch-beginner

pytorch tutorial for beginners

graph_nets

Build Graph Nets in Tensorflow

Auto-CNN-HSI-Classification

Code for the paper "Automatic Design of Convolutional Neural Network for Hyperspectral Image Classification"

Conv-Caps-HSI-Classification

Code for the paper "Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification"

GCN

Graph Convolutional Neural Network Hashing

tensorflow2_tutorials_chinese

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

IterNorm-pytorch

This is the pytorch re-implementation of the IterNorm

powerful-gnns

How Powerful are Graph Neural Networks?

ImageNet_Dataset

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

Congenitally-Blind-Model

CBM Repo for <Listen to the Image>

pytorch-grad-cam

PyTorch implementation of Grad-CAM

CoolingTeslaK80

Arduino PWM Fan Control for Tesla K80

keras-grad-cam

An implementation of Grad-CAM with keras

FastGCN

The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""

Composite-Quantization-for-Approximate-Nearest-Neighbor-Search

Implemented the Composite Quantization algorithm for Nearest Neighbor search and performed analysis on SIFT, GIST and MNIST datasets.

tcav_nlp

"Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)" paper implementation

PySGWT

Spectral Graph Wavelet Transform

Representer_Point_Selection

code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018

tcav_pytorch

Pytorch implementation of Google TCAV

keras-docs-zh

PDF version of the Keras Chinese (zh-cn) translation docs

graphwave

IBD

IBD: Interpretable Basis Decomposition for Visual Explanation