109 Open source projects that are alternatives of or similar to Entity-Graph-VLN

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Demo of RouteNet in ACM SIGCOMM'19

Summary of open source code for deep learning models in the field of traffic prediction

Implement of DiGCN, NeurIPS-2020

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

Source code and datasets for ACL 2020 paper: Neighborhood Matching Network for Entity Alignment.

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

Disentagnled Graph Collaborative Filtering, SIGIR2020

⌛ Introducing Self-Attention to Target Attentive Graph Neural Networks (AISP '22)

GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

Graph Neural Networks with Keras and Tensorflow 2.

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

links to conference publications in graph-based deep learning

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Inductive relation prediction by subgraph reasoning, ICML'20

Visualization tool for Graph Neural Networks

Code for NAACL 2021 paper: MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences

Summary of social recommendation papers and codes

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Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks

Fast Image Retrieval (FIRe) is an open source project to promote image retrieval research. It implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020

From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)

An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).

StellarGraph - Machine Learning on Graphs

Code and resources on scalable and efficient Graph Neural Networks

Graph Neural Network Library for PyTorch

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

Python package built to ease deep learning on graph, on top of existing DL frameworks.

GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

Implementation of Directional Graph Networks in PyTorch and DGL

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Implementation of "Overlapping Community Detection with Graph Neural Networks"

Material for the EPFL master course "A Network Tour of Data Science", edition 2019.

Graph-based Deep Q Network for Web Navigation

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Combining relational context and relational paths for knowledge graph completion

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

Combining relational context and relational paths for knowledge graph completion

Code and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

odr.chalmers.se/handle/20.500.12380/256629?locale=en

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

A reading list for deep graph learning acceleration.

The official code and datasets for "Zero-Shot Multi-View Indoor Localization via Graph Location Networks" (ACMMM 2020)

Code and data of the Fine-Grained R2R Dataset proposed in the EMNLP 2021 paper Sub-Instruction Aware Vision-and-Language Navigation

Subgraph Neural Networks (NeurIPS 2020)

Official implementation of CATs

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning