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graph-convolutional-neural-networks

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weihua916 /powerful-gnns

How Powerful are Graph Neural Networks?

deep-learning graph-neural-networks graph-convolutional-neural-networks

UpdatedJul 1, 2021
Python

SuperBruceJia /EEG-DL

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

deep-learning tensorflow transformers cnn transformer lstm gru rnn densenet resnet eeg-data one-shot-learning attention-mechanism motor-imagery-classification residual-learning fully-convolutional-networks gcn eeg-classification eeg-signals-processing graph-convolutional-neural-networks

UpdatedJul 20, 2025
Python

APPNP

benedekrozemberczki /APPNP

A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

machine-learning deep-neural-networks research deep-learning pagerank pytorch deepwalk attention network-embedding gcn iclr node2vec graph-embedding graph-classification node-embedding graph-attention graph-convolutional-neural-networks graph-neural-network ppnp appnp

UpdatedNov 6, 2022
Python

maggie0106 /Graph-CNN-in-3D-Point-Cloud-Classification

Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)

graph point-cloud convolutional-neural-networks graph-convolutional-networks gcn pointcloud gcnn graph-convolutional-network graph-cnn 3d-classification graph-convolutional-neural-networks

UpdatedSep 19, 2018
Python

huawei-noah /BGCN

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

gcn bayesian-neural-networks graph-convolutional-network graph-learning graph-neural-networks graph-convolutional-neural-networks gnn bayesian-graph-neural-networks

UpdatedSep 8, 2019
Python

UttaranB127 /STEP

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

dataset dataset-generation affective-computing graph-convolutional-networks emotion-detection emotion-recognition variational-autoencoder gait conditional-vae gait-analysis gait-recognition graph-convolutional-neural-networks conditional-variational-autoencoder spatial-temporal-action-detection emotion-perception

UpdatedDec 8, 2022
Python

Frank-LIU-520 /DeepMoleNet

Deep learning for molecules quantum chemistry properties prediction

deep-learning quantum-chemistry quantum-machine-learning graph-convolutional-neural-networks

UpdatedApr 14, 2021
Python

rctzeng /ICML19-EgoCNN

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

convolutional-neural-networks self-similarity interpretability icml graph-embeddings scale-free-networks graph-neural-networks graph-networks graph-convolutional-neural-networks icml-2019

UpdatedAug 24, 2021
Python

BDBC-KG-NLP /Covolution_over_Dependency_Tree_EMNLP2019

Here is the code for the paper ``Aspect-Level Sentiment Analysis via Convolution over Dependency Tree'' accepted by EMNLP2019.

aspect-based-sentiment-analysis graph-convolutional-neural-networks

UpdatedNov 18, 2021
Python

farkoo /GNN-Citations

Node Classification with Graph Neural Networks

node-classification graph-neural-networks centrality-measures graph-convolutional-neural-networks gnn feedforward-neural-networks

UpdatedJan 27, 2022
Jupyter Notebook

XzrTGMu /twin-nphard

Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems

combinatorics heuristics greedy-algorithms steiner-tree connected-dominating-set distributed-algorithms graph-convolutional-networks steiner-tree-problem combinatorial-optimization approximation-algorithms distributed-algorithm deterministic-policy-gradients twin-networks graph-neural-networks minimum-weighted-dominating-set graph-convolutional-neural-networks maximum-weighted-independent-set node-weighted-steiner-tree moser-tardos-algorithm twin-based-critic

UpdatedMar 8, 2024
Jupyter Notebook

withai /Docked-protein-Interaction-ranking-using-graph-neural-networks

A deep learning library to rank protein complexes using graph neural networks

pytorch neural-networks protein-interaction graph-neural-networks graph-convolutional-neural-networks graph-attention-network protein-interaction-ranking

UpdatedAug 26, 2020
Python

RussH-code /Graph-Convolutional-Neural-Network-GCN

deep-learning keras-tensorflow gcn cora-dataset graph-convolutional-neural-networks node-embeddings stellargraph-library

UpdatedJul 19, 2021
Jupyter Notebook

withai /Graph-Neural-Networks

A deep learning library for graph data structures

deep-learning neural-networks graph-attention-networks graph-neural-networks graph-convolutional-neural-networks

UpdatedJun 5, 2020
Python

KhaiTTNguyen /Computational_Quantum_Chemistry

deep-learning excited-states graph-convolutional-neural-networks absorption-spectra

UpdatedJul 28, 2021
Jupyter Notebook

caldi99 /Learning-From-Network-Project

text-classification recurrent-neural-networks convolutional-neural-networks support-vector-machines unipd boosting bagging graph-neural-networks dei graph-convolutional-neural-networks dei-unipd rocchio-classifier

UpdatedJan 17, 2023
Python

nmdl-mizo /lcaonet

LCAONet - MPNN including electronic structure and orbital information, physically motivatied by the LCAO method.

machine-learning deep-learning pytorch materials-informatics graph-neural-networks graph-convolutional-neural-networks machine-learning-interatomic-potential

UpdatedNov 8, 2023
Python

itskalvik /2s-AGCN

Unofficial Tensorflow implementation of the CVPR'19 paper "Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition"

tensorflow ntu-rgbd skeleton-based-action-recognition graph-convolutional-neural-networks

UpdatedDec 31, 2019
Python

riccardocadei /GraphML-Contest-2019-Oracle-PoliMI

Multi‑label vertex classification on a protein‑protein interaction network generating a powerful embedding of its graph - @ Oracle Labs, Politecnico di Milano

semi-supervised-learning graph-convolutional-neural-networks

UpdatedJul 21, 2021
Jupyter Notebook

pranay-5374 /Sign-Language-Recognition-using-CNN-and-GCN

This project focuses on sign language recognition, using WLASL dataset for training models—one with CNN and the other with TGCN. The goal is to improve communication between the deaf and hearing communities, with potential applications in assistive technologies, education, and human-computer interaction.

computer-vision deep-learning convolutional-neural-networks graph-convolutional-neural-networks

UpdatedJul 27, 2023
Jupyter Notebook

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