Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences

Overview

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences

This repository is an official PyTorch implementation of Neighbor2Seq.

Meng Liu and Shuiwang Ji. Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences [SDM2022].

Requirements

  • PyTorch
  • PyTorch Geometric (with 1.6.1-1.7.2 recommended)
  • OGB

Reference

@inproceedings{liu2022neighbor2seq,
  title={{Neighbor2Seq}: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences},
  author={Liu, Meng and Ji, Shuiwang},
  booktitle={Proceedings of the 2022 SIAM International Conference on Data Mining},
  year={2022},
  organization={SIAM}
}

Run

All of our running scripts are included in run_ours.sh. An example on Flickr is as follows.

  • Step 1: Precompute Neighbor2Seq
python precompute.py --dataset=Flickr --P=10 --add_self_loop=True
  • Step 2: Train and evaluate Neighbor2Seq+Conv or Neighbor2Seq+Attn
CUDA_VISIBLE_DEVICES=0 python main_inductive.py --model=conv --lr=0.0008 --K=10 --weight_decay=0.00005 --hidden=256 --dropout=0.5 --batch_size=24576 --epochs=400 --kernel_size=7 --runs=10 --log_step=1 
CUDA_VISIBLE_DEVICES=0 python main_inductive.py --model=posattn --lr=0.002 --K=10 --weight_decay=0.00005 --hidden=256 --dropout=0.5 --batch_size=256 --epochs=200 --pe_drop=0.25 --runs=10 --log_step=1

Results

  • Results on inductive tasks: Reddit, Flickr, and Yelp

  • Results on ogbn-papers100M

  • Results on ogbn-products

Owner
DIVE Lab, Texas A&M University
DIVE Lab, Texas A&M University
To SMOTE, or not to SMOTE?

To SMOTE, or not to SMOTE? This package includes the code required to repeat the experiments in the paper and to analyze the results. To SMOTE, or not

Amazon Web Services 1 Jan 03, 2022
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation (CVPR 2021)

Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Input Image Initial CAM Successive Maps with adversar

Jungbeom Lee 110 Dec 07, 2022
HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks

HiFiGAN Denoiser This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep F

Rishikesh (ऋषिकेश) 134 Dec 27, 2022
Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021

NPMs: Neural Parametric Models Project Page | Paper | ArXiv | Video NPMs: Neural Parametric Models for 3D Deformable Shapes Pablo Palafox, Aljaz Bozic

PabloPalafox 109 Nov 22, 2022
Using LSTM to detect spoofing attacks in an Air-Ground network

Using LSTM to detect spoofing attacks in an Air-Ground network Specifications IDE: Spider Packages: Tensorflow 2.1.0 Keras NumPy Scikit-learn Matplotl

Tiep M. H. 1 Nov 20, 2021
Time should be taken seer-iously

TimeSeers seers - (Noun) plural form of seer - A person who foretells future events by or as if by supernatural means TimeSeers is an hierarchical Bay

279 Dec 26, 2022
TensorFlow implementation of ENet, trained on the Cityscapes dataset.

segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e

Fredrik Gustafsson 248 Dec 16, 2022
Code for the TASLP paper "PSLA: Improving Audio Tagging With Pretraining, Sampling, Labeling, and Aggregation".

PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation Introduction Getting Started FSD50K Recipe AudioSet Recipe Label E

Yuan Gong 84 Dec 27, 2022
A PyTorch re-implementation of the paper 'Exploring Simple Siamese Representation Learning'. Reproduced the 67.8% Top1 Acc on ImageNet.

Exploring simple siamese representation learning This is a PyTorch re-implementation of the SimSiam paper on ImageNet dataset. The results match that

Taojiannan Yang 72 Nov 09, 2022
[CVPR'21] Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-view Transformation

Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-view Transformation Weixiang Yang, Qi Li, Wenxi Liu, Yuanlong Yu, Y

118 Dec 26, 2022
Using Hotel Data to predict High Value And Potential VIP Guests

Description Using hotel data and AI to predict high value guests and potential VIP guests. Hotel can leverage on prediction resutls to run more effect

HCG 12 Feb 14, 2022
Mengzi Pretrained Models

中文 | English Mengzi 尽管预训练语言模型在 NLP 的各个领域里得到了广泛的应用,但是其高昂的时间和算力成本依然是一个亟需解决的问题。这要求我们在一定的算力约束下,研发出各项指标更优的模型。 我们的目标不是追求更大的模型规模,而是轻量级但更强大,同时对部署和工业落地更友好的模型。

Langboat 424 Jan 04, 2023
Tandem Mass Spectrum Prediction with Graph Transformers

MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv

Röst Lab 13 Oct 27, 2022
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

Differential Privacy (DP) Based Federated Learning (FL) Everything about DP-based FL you need is here. (所有你需要的DP-based FL的信息都在这里) Code Tip: the code o

wenzhu 83 Dec 24, 2022
CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery

CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery This paper (CoANet) has been published in IEEE TIP 2021. This code i

Jie Mei 53 Dec 03, 2022
Gapmm2: gapped alignment using minimap2 (align transcripts to genome)

gapmm2: gapped alignment using minimap2 This tool is a wrapper for minimap2 to r

Jon Palmer 2 Jan 27, 2022
Direct design of biquad filter cascades with deep learning by sampling random polynomials.

IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe

Christian J. Steinmetz 55 Nov 02, 2022
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [2021]

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit

Wouter Van Gansbeke 80 Nov 20, 2022
RLHive: a framework designed to facilitate research in reinforcement learning.

RLHive is a framework designed to facilitate research in reinforcement learning. It provides the components necessary to run a full RL experiment, for both single agent and multi agent environments.

88 Jan 05, 2023
Source code for the NeurIPS 2021 paper "On the Second-order Convergence Properties of Random Search Methods"

Second-order Convergence Properties of Random Search Methods This repository the paper "On the Second-order Convergence Properties of Random Search Me

Adamos Solomou 0 Nov 13, 2021