Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Related tags

Deep LearningDGCN
Overview

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Setup

This implementation is based on PyTorch >= 1.0.0. Small dataset (including Cora, Citeseer, and Pubmed) are located in the data folder.

Usage

Please use the jupyter notebook files localed in the ./jupyter_notebooks. Please copy the file you want to run to the root folder, i.e., ./DGCN/CODE_WANT_TO_RUN.ipynb, then directly run it using jupyter notebook.

Owner
Weilin Cong
Graduate student at Pennsylvania State University.
Weilin Cong
Siamese TabNet

Raifhack-DS-2021 https://raifhack.ru/ - Команда Звёздочка Siamese TabNet Сиамская TabNet предсказывает стоимость объекта недвижимости с price_type=1,

Daniel Gafni 15 Apr 16, 2022
SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

SciKit-Learn Laboratory This Python package provides command-line utilities to make it easier to run machine learning experiments with scikit-learn. O

ETS 528 Nov 25, 2022
This is a simple backtesting framework to help you test your crypto currency trading. It includes a way to download and store historical crypto data and to execute a trading strategy.

You can use this simple crypto backtesting script to ensure your trading strategy is successful Minimal setup required and works well with static TP a

Andrei 154 Sep 12, 2022
High frequency AI based algorithmic trading module.

Flow Flow is a high frequency algorithmic trading module that uses machine learning to self regulate and self optimize for maximum return. The current

59 Dec 14, 2022
Build Graph Nets in Tensorflow

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact DeepMind 5.2k Jan 05, 2023

Matplotlib Image labeller for classifying images

mpl-image-labeller Use Matplotlib to label images for classification. Works anywhere Matplotlib does - from the notebook to a standalone gui! For more

Ian Hunt-Isaak 5 Sep 24, 2022
Implementation of our paper 'RESA: Recurrent Feature-Shift Aggregator for Lane Detection' in AAAI2021.

RESA PyTorch implementation of the paper "RESA: Recurrent Feature-Shift Aggregator for Lane Detection". Our paper has been accepted by AAAI2021. Intro

137 Jan 02, 2023
Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.

This repository contains the code release for Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields. This implementation is written in JAX, and is a fork of Google's JaxNeRF

Google 625 Dec 30, 2022
UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac protocols on unmanned aerial vehicle networks.

UAV-Networks Simulator - Autonomous Networking - A.A. 20/21 UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac pr

0 Nov 13, 2021
pytorchのスライス代入操作をonnxに変換する際にScatterNDならないようにするサンプル

pytorch_remove_ScatterND pytorchのスライス代入操作をonnxに変換する際にScatterNDならないようにするサンプル。 スライスしたtensorにそのまま代入してしまうとScatterNDになるため、計算結果をcatで新しいtensorにする。 python ver

2 Dec 01, 2022
This repository includes code of my study about Asynchronous in Frequency domain of GAN images.

Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images Binh M. Le & Simon S. Woo, "Exploring the Asynchronous of the Frequ

4 Aug 06, 2022
Example of a Quantum LSTM

Example of a Quantum LSTM

Riccardo Di Sipio 36 Oct 31, 2022
基于深度强化学习的原神自动钓鱼AI

原神自动钓鱼AI由YOLOX, DQN两部分模型组成。使用迁移学习,半监督学习进行训练。 模型也包含一些使用opencv等传统数字图像处理方法实现的不可学习部分。

4.2k Jan 01, 2023
Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains

Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains This is an accompanying repository to the ICAIL 2021 pap

4 Dec 16, 2021
Generating Videos with Scene Dynamics

Generating Videos with Scene Dynamics This repository contains an implementation of Generating Videos with Scene Dynamics by Carl Vondrick, Hamed Pirs

Carl Vondrick 706 Jan 04, 2023
thundernet ncnn

MMDetection_Lite 基于mmdetection 实现一些轻量级检测模型,安装方式和mmdeteciton相同 voc0712 voc 0712训练 voc2007测试 coco预训练 thundernet_voc_shufflenetv2_1.5 input shape mAP 320

DayBreak 39 Dec 05, 2022
Server files for UltimateLabeling

UltimateLabeling server files Server files for UltimateLabeling. git clone https://github.com/alexandre01/UltimateLabeling_server.git cd UltimateLabel

Alexandre Carlier 4 Oct 10, 2022
Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.

Doubly Trained Neural Machine Translation System for Adversarial Attack and Data Augmentation Languages Experimented: Data Overview: Source Target Tra

Steven Tan 1 Aug 18, 2022
Adversarial Learning for Modeling Human Motion

Adversarial Learning for Modeling Human Motion This repository contains the open source code which reproduces the results for the paper: Adversarial l

wangqi 6 Jun 15, 2021
Code to reproduce the results in the paper "Tensor Component Analysis for Interpreting the Latent Space of GANs".

Tensor Component Analysis for Interpreting the Latent Space of GANs [ paper | project page ] Code to reproduce the results in the paper "Tensor Compon

James Oldfield 4 Jun 17, 2022