Topic: gnns Goto Github
Some thing interesting about gnns
Some thing interesting about gnns
gnns,DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging (PyTorch implementation)
User: adriansroman
gnns,This repository contains the code for the work on protein-ligand interaction with GNNs and XAI
User: andmastro
gnns,Awesome De novo drugs design papers
User: asarigun
gnns,Official Implementation of Graph Mixer Networks
User: asarigun
Home Page: https://arxiv.org/abs/2301.12493
gnns,List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning
User: aspirincode
gnns,Interface-aware molecular generative framework for protein-protein interaction modulators
User: aspirincode
gnns,List of Molecular and Material design using Generative AI and Deep Learning
User: aspirincode
gnns,Brain graph super-resolution using graph neural networks.
User: basiralab
gnns,A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.
User: basiralab
gnns,HADA (Hiearachical Adversarial Domain Alignment) for brain graph prediction and classification.
User: basiralab
gnns,Multigraph generation from a source graph.
User: basiralab
gnns,An implementation of the Autoregressive Diffusion Model for Graph Generation from [Kong et al. 2023]
User: caio-freitas
gnns,A Note On Over-Smoothing for Graph Neural Network
User: chen-cai-osu
gnns,Pytorch Geometric implementation of the "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" paper.
User: claudmor
gnns,Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)
User: cszhangzhen
gnns,Official code for [Neurips23] MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
User: dhh1995
Home Page: https://sites.google.com/view/megraph
gnns,DiTEC research
Organization: ditec-project
gnns,Re-implementation and extension of the work described in "Learning to Represent Programs with Graphs"
User: dmitrykazhdan
gnns,Graph Neural Network (GNN) emulation of the left-ventricle (LV) in diastole
User: dodaltuin
gnns,FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.
Organization: fedml-ai
Home Page: https://arxiv.org/abs/2104.07145
gnns,Investigating the extent to which structural encodings in geometric methods contribute in capturing topological information and developing a generic framework (ToGePi) to inject topological and geometric information into MPNN architectures.
User: gerardplanella
gnns,A Survey of Learning from Graphs with Heterophily
User: gongchenghua
gnns,PyPi module for Graphlet AI Knowledge Graph Factory
Organization: graphlet-ai
Home Page: https://graphlet.ai
gnns,Full Stack Graph Machine Learning: Theory, Practice, Tools and Techniques
Organization: graphlet-ai
Home Page: https://graphlet.ai
gnns,Papers on the topic of large language models (LLMs) on graphs
User: jianglin954
Home Page: https://jianglin954.github.io/Awesome-Large-Language-Models-On-Graphs/
gnns,Implementation of "SALSA-CLRS: A Sparse and Scalable Benchmark for Algorithmic Reasoning". SALSA-CLRS is an extension to the original clrs package, prioritizing scalability and the utilization of sparse representations. It provides pytorch based PyG datasets and dataloaders.
User: jkminder
gnns,GNNs in Recommendation Systems
User: jockwang
gnns,[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
User: junxia97
gnns,Predict binding affinity of ligand-protein complexes using Graph Neural Networks. The model is implemented using PyTorch Geometric and based on the method in "Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks"
User: kthrn22
Home Page: https://pubs.acs.org/doi/abs/10.1021/acs.jcim.9b00387
gnns,[ACM Computing Surveys'23] Implementations or refactor of some temporal link prediction/dynamic link prediction methods and summary of related open resources for survey paper "Temporal Link Prediction: A Unified Framework, Taxonomy, and Review" which has been accepted by ACM Computing Surveys.
User: kuroginqin
gnns,[3DV21] Visual Camera Re-Localization Using Graph Neural Networks and Relative Pose Supervision, M. Türkoǧlu et al.
Organization: nianticlabs
gnns,Solving the Job-Shop Scheduling Problem (JSSP) with Graph Neural Networks (GNNs).
User: pabloo22
gnns,HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method)
User: qbxlvnf11
gnns,This repository stores the code implemented to generate the results of our paper: Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors
User: rayn2402
gnns,graph neural networks, information theory, AI for Sciences
User: samyu0304
gnns,Edge-Augmented Graph Transformer
User: shamim-hussain
gnns,Official code for the SDM2022 paper -- SSSNET: Semi-Supervised Signed Network Clustering.
User: sherylhyx
gnns,Presented as tutorial at the Second Learning on Graphs Conference (LoG 2023)
Organization: sisinflab
Home Page: https://sisinflab.github.io/tutorial-gnns-recsys-log2023/
gnns,Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
Organization: tech-srl
gnns,NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.
Organization: usc-infolab
gnns,A weekly list of interesting reads related to deep learning found by our group members!
Organization: vlgiitr
gnns,3D Face Classification with Graph Neural Networks
User: w00zie
gnns,MatTen: Equivariant Graph Neural Nets for Tensorial Properties of Materials
Organization: wengroup
Home Page: https://doi.org/10.1039/D3DD00233K
gnns,Python Framework for An Investigation into Unsupervised GNN Learning Environments
User: willleeney
gnns,3D Graph Neural Networks for RGBD Semantic Segmentation
User: yanx27
gnns,Implementation for ReFactor GNNs
User: yihong-chen
gnns,Bags of Tricks in OGB (node classification) with GCNs.
User: ytchx1999
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