218 Open source projects that are alternatives of or similar to DiGCN

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

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

Smart Contract Vulnerability Detection Using Graph Neural Networks (IJCAI-20 Accepted)

A reading list for deep graph learning acceleration.

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

This is a paper list about Resource Allocation in Network Functions Virtualization (NFV) and Software-Defined Networking (SDN).

Pseudo-Label: Semi-Supervised Learning on CIFAR-10 in Keras

TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

JCLAL is a general purpose framework developed in Java for Active Learning.

SPEAR: Programmatically label and build training data quickly.

Geometric Deep Learning for Flux

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)

noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

Adversarial Distributional Training (NeurIPS 2020)

Semi-Supervised Learning and Collective Classification

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

This is a Pytorch implementation of GraphLIME

An implementation for our paper: CsiGAN: Robust Channel State Information-based Activity Recognition with GANs (IEEE Internet of Things Journal, 2019), which is the semi-supervised Generative Adversarial Network (GAN) for Channel State Information (CSI) -based activity recognition.

Representing Long-Range Context for Graph Neural Networks with Global Attention

[COLING 2020] Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis

[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

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

Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning

Benchmarks for semi-supervised domain generalization.

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

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

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)

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

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace

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

Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (INFORMS Annual Meeting Session 2019)

Official code for "Self-Supervised driven Consistency Training for Annotation Efficient Histopathology Image Analysis" Published in Medical Image Analysis (MedIA) Journal, Oct, 2021.

Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

[CVPR21] Implementation of our work "Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation"

Supervised community detection with line graph neural networks

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

Semi-supervised Learning GAN

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

Source code and data for ACL 2019 Long Paper ``Semantic Parsing with Dual Learning".

No description or website provided.

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Code & data accompanying the ICLR 2020 paper "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation"

The GAP package Semigroups

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks

Joint Semi-supervised Learning of Image Registration and Segmentation

A spherical convolutional neural network for cosmology (TFv1).

Combining relational context and relational paths for knowledge graph completion

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Code accompanying the paper "Semi-supervised adversarial audio source separation applied to singing voice extraction"

Probabilistic Type Inference using Graph Neural Networks

90%+ with 40 labels. please see the readme for details.

Graph-based machine learning for chemical property prediction

Papers about explainability of GNNs

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).

Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"

Implementation of Temporal Ensembling for Semi-Supervised Learning by Laine et al. with tensorflow eager execution

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