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Graph Neural Network

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/koustav123/aesthetics_assessment_using_graphs

공식 코드

Image Aesthetics Assessment Using Graph Attention Network

https://github.com/kracr/reonto-relation-extraction

공식 코드

ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extraction

https://github.com/krishnaswamylab/dymag

공식 코드

DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms

https://github.com/ksgr5566/unsegarmanet

공식 코드

UnSeGArmaNet: Unsupervised Image Segmentation using Graph Neural Networks with Convolutional ARMA Filters

https://github.com/kumarrobotics/coveragecontrol

공식 코드

LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Control

https://github.com/kunzhan/sdsne

공식 코드

Stationary Diffusion State Neural Estimation for Multiview Clustering

https://github.com/kxchern/dkepool-tsa

공식 코드

Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System

https://github.com/kyle-one/signa

공식 코드

Semantic Interleaving Global Channel Attention for Multilabel Remote Sensing Image Classification

https://github.com/kyleenliao/Prescribed_Fire_PM2.5_Simulation

공식 코드

Simulating the Air Quality Impact of Prescribed Fires Using Graph Neural Network-Based PM$_{2.5}$ Forecasts

https://github.com/kyonofx/mlcgmd

공식 코드

Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-Scale Graph Networks

https://github.com/laiweijiang/VAGNN

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A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation

https://github.com/lamm-mit/materiomictransformer

공식 코드

Generative Pretrained Autoregressive Transformer Graph Neural Network applied to the Analysis and Discovery of Novel Proteins

https://github.com/lars-research/adaprop

공식 코드

AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning

https://github.com/lars-research/emergnn

공식 코드

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network

https://github.com/lars-research/knowddi

공식 코드

Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning

https://github.com/lars-research/pacia

공식 코드

PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction

https://github.com/larsbentsen/fftransformer

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Spatio-Temporal Wind Speed Forecasting using Graph Networks and Novel Transformer Architectures

https://github.com/lascavana/objvalprediction

공식 코드

Learning optimal objective values for MILP

https://github.com/latentgnn/LatentGNN-V1-PyTorch

공식 코드

LatentGNN: Learning Efficient Non-local Relations for Visual Recognition

https://github.com/laurencee9/structural_pertubation_detection

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Detecting structural perturbations from time series with deep learning

https://github.com/lbcb-sci/gnns-hamiltonian-cycles

공식 코드

Finding Hamiltonian cycles with graph neural networks

https://github.com/lcai2/stea

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A Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs

https://github.com/lcosmo/DGM_pytorch

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Differentiable Graph Module (DGM) for Graph Convolutional Networks

https://github.com/learningmatter-mit/alchemical-mlip

공식 코드

Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials

https://github.com/leolouis14/kucnet

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Knowledge-Enhanced Recommendation with User-Centric Subgraph Network

https://github.com/leosampaio/scene-designer

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Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch

https://github.com/leson502/CORECT_EMNLP2023

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Conversation Understanding using Relational Temporal Graph Neural Networks with Auxiliary Cross-Modality Interaction

https://github.com/lexpk/logicaldistillationofgnns

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Logical Distillation of Graph Neural Networks

https://github.com/lgalke/lifelong-learning

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Lifelong Learning on Evolving Graphs Under the Constraints of Imbalanced Classes and New Classes

https://github.com/lijunxian111/UIGNN

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Uncertainty-aware Traffic Prediction under Missing Data

https://github.com/likojack/odam

공식 코드

ODAM: Object Detection, Association, and Mapping using Posed RGB Video

https://github.com/limresgrp/herobm

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HEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations

https://github.com/litong99/xpath

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Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network

https://github.com/liu-jc/mgnni

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MGNNI: Multiscale Graph Neural Networks with Implicit Layers

https://github.com/liuchuang0059/gradformer

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Gradformer: Graph Transformer with Exponential Decay

https://github.com/liuchuang0059/hi-gmae

공식 코드

Hi-GMAE: Hierarchical Graph Masked Autoencoders

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