https://github.com/perubhardwaj/attributionattack
공식 코드Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods
Papers with Code 아카이브
Link Prediction
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Link Prediction is a task in graph and network analysis where the goal is to predict missing or future connections between nodes in a network. Given a partially observed network, the goal of link prediction is to infer which links are most likely to be added or missing based on the observed connections and the structure of the network.
<span style="color:grey; opacity: 0.6">( Image credit: Inductive Representation Learning on Large Graphs )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/perubhardwaj/inferenceattack
공식 코드Poisoning Knowledge Graph Embeddings via Relation Inference Patterns
https://github.com/petergriffinjin/edgeformers
공식 코드Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
https://github.com/petergriffinjin/heterformer
공식 코드Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks
https://github.com/peyman-bi/sattle
공식 코드Self-attention Presents Low-dimensional Knowledge Graph Embeddings for Link Prediction
https://github.com/pfranciscovalente/science4cast_topological
공식 코드Link Prediction of Artificial Intelligence Concepts using Low Computational Power
https://github.com/phanchauthang/dsaa-2023-kaggle
공식 코드Link Prediction for Wikipedia Articles as a Natural Language Inference Task
https://github.com/phucdoitoan/inter-domain_lp
공식 코드https://github.com/phython96/ARGNP
공식 코드https://github.com/pige99/TME
공식 코드TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation
https://github.com/pku-dair/nafs
공식 코드NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning
https://github.com/pkusjh/lass
공식 코드Joint Language Semantic and Structure Embedding for Knowledge Graph Completion
https://github.com/pkuyzy/TLC-GNN
공식 코드Link Prediction with Persistent Homology: An Interactive View
https://github.com/pldlgb/MetaSD
공식 코드Self-Distillation with Meta Learning for Knowledge Graph Completion
https://github.com/plumdeq/neuro-kglink
공식 코드https://github.com/pmernyei/wiki-cs-dataset
공식 코드Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks
https://github.com/pnnl/SLICE
공식 코드Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
https://github.com/pouyapez/criage
공식 코드Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications
https://github.com/pouyapez/mkbe
공식 코드Embedding Multimodal Relational Data for Knowledge Base Completion
https://github.com/prakhargurawa/Drug-Similarity-and-Link-Prediction-using-Graph-Embeddings-on-Medical-Knowledge-Graph
공식 코드Drug Similarity and Link Prediction Using Graph Embeddings on Medical Knowledge Graphs
https://github.com/predict-idlab/RR-GCN
공식 코드https://github.com/purdueminds/isdea
공식 코드Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Types
https://github.com/pyg-team/pytorch_geometric
공식 코드What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
https://github.com/pykeen/ilpc2022
공식 코드An Open Challenge for Inductive Link Prediction on Knowledge Graphs
https://github.com/pykeen/pykeen
공식 코드PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
https://github.com/pykeen/ranking-metrics-manuscript
공식 코드A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs
https://github.com/qianghuangwhu/benchtemp
공식 코드BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
https://github.com/qiaoyu-tan/ps2
공식 코드Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection
https://github.com/quark0/ANALOGY
공식 코드https://github.com/quentin-duchemin/Markovian-random-geometric-graph
공식 코드Markov Random Geometric Graph (MRGG): A Growth Model for Temporal Dynamic Networks
https://github.com/quentin-duchemin/inference-markovian-SBM
공식 코드Reliable Time Prediction in the Markov Stochastic Block Model
https://github.com/quqxui/mpikgc
공식 코드Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models
https://github.com/rahuln/lm-bio-kgc
공식 코드Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study
https://github.com/rakshit-agrawal/LEAP
공식 코드https://github.com/ralphabb/BoxE
공식 코드https://github.com/rampasek/GraphGPS
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.