Papers with Code 아카이브

Graph Neural Network

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

1

코드

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

https://github.com/parajain/dynamic_context

공식 코드

Conversational Semantic Parsing using Dynamic Context Graphs

https://github.com/parksandrecfan/bignet-car

공식 코드

Automating Style Analysis and Visualization With Explainable AI -- Case Studies on Brand Recognition

https://github.com/parksandrecfan/bignet-phone

공식 코드

Automating Style Analysis and Visualization With Explainable AI -- Case Studies on Brand Recognition

https://github.com/pasalab/autoac

공식 코드

AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network

https://github.com/pathpy/pathpyg

공식 코드

Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs

https://github.com/paulhausner/neural-incomplete-factorization

공식 코드

Learning incomplete factorization preconditioners for GMRES

https://github.com/pengxingang/pocket2mol

공식 코드

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

https://github.com/penlu/bespoke-gnn4do

공식 코드

Are Graph Neural Networks Optimal Approximation Algorithms?

https://github.com/pfnet-research/chainer-chemistry

공식 코드

Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks in Molecular Graph Analysis

https://github.com/pg2455/Hybrid-learn2branch

공식 코드

Hybrid Models for Learning to Branch

https://github.com/pietrobarbiero/digital-patient

공식 코드

Graph representation forecasting of patient's medical conditions: towards a digital twin

https://github.com/pkang2017/tactilelsn

공식 코드

Boost Event-Driven Tactile Learning with Location Spiking Neurons

https://github.com/pkuyzy/TLC-GNN

공식 코드

Link Prediction with Persistent Homology: An Interactive View

https://github.com/pnnl/FragNet

공식 코드

FragNet: A Graph Neural Network for Molecular Property Prediction with Four Levels of Interpretability

https://github.com/pnnl/chemreasoner

공식 코드

ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback

https://github.com/pnnl/downstream_mol_gnn

공식 코드

Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators

https://github.com/pnnl/mol_dgnn

공식 코드

Geometric learning of the conformational dynamics of molecules using dynamic graph neural networks

https://github.com/polimi-ispl/magcrn

공식 코드

Back to the Future: GNN-based NO$_2$ Forecasting via Future Covariates

https://github.com/pqros/fastcover

공식 코드

FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks

https://github.com/prash29/lager

공식 코드

Towards Few-shot Entity Recognition in Document Images: A Graph Neural Network Approach Robust to Image Manipulation

https://github.com/princeton-vl/attach-juxtapose-parser

공식 코드

Strongly Incremental Constituency Parsing with Graph Neural Networks

https://github.com/projectultra/GCBLANE

공식 코드

GCBLANE: A graph-enhanced convolutional BiLSTM attention network for improved transcription factor binding site prediction

https://github.com/prometheusXN/LADAN

공식 코드

Distinguish Confusing Law Articles for Legal Judgment Prediction

https://github.com/prometheusXN/MR-GNN

공식 코드

MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions

https://github.com/proroklab/ModGNN

공식 코드

ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture

https://github.com/proroklab/gnngls

공식 코드

Graph Neural Network Guided Local Search for the Traveling Salesperson Problem

https://github.com/proroklab/hetgppo

공식 코드

Heterogeneous Multi-Robot Reinforcement Learning

https://github.com/proroklab/vectorizedmultiagentsimulator

공식 코드

Heterogeneous Multi-Robot Reinforcement Learning

https://github.com/provenanceanalytics/kairos

공식 코드

Kairos: Practical Intrusion Detection and Investigation using Whole-system Provenance

https://github.com/publiccoderepo/SMP_GNN_Quant

공식 코드

Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation

https://github.com/pyg-team/pytorch_geometric

공식 코드

Do We Need Anisotropic Graph Neural Networks?

https://github.com/pyt-team/TopoBenchmarkX

공식 코드

TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks

https://github.com/q-rz/kdd23-ditto

공식 코드

Reconstructing Graph Diffusion History from a Single Snapshot

https://github.com/q1park/spacetime

공식 코드

Moment-Matching Graph-Networks for Causal Inference

https://github.com/qcydm/vgaer

공식 코드

VGAER: Graph Neural Network Reconstruction based Community Detection

https://github.com/qiankunmu/hdhgn

공식 코드

Heterogeneous Directed Hypergraph Neural Network over abstract syntax tree (AST) for Code Classification

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.