Papers with Code 아카이브
Relational Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 1
The goal of Relational Reasoning is to figure out the relationships among different entities, such as image pixels, words or sentences, human skeletons or interactive moving agents.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pavliclab/aaai2022-clear2022-visual_relationship_detection-rwfn
공식 코드https://github.com/pkumod/vgstore
공식 코드VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph
https://github.com/purdueminds/isdea
공식 코드Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Types
https://github.com/rasmusbergpalm/recurrent-relational-networks
공식 코드https://github.com/robinzixuan/Video-Question-Answering-HRI
공식 코드Open-Ended Multi-Modal Relational Reasoning for Video Question Answering
https://github.com/rstriv/Know-Evolve
공식 코드Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
https://github.com/rusty1s/pytorch_geometric
공식 코드https://github.com/shamikroy/moral-role-prediction
공식 코드Identifying Morality Frames in Political Tweets using Relational Learning
https://github.com/shaneshang/simplifiedrpm-visual-reasoning
공식 코드https://github.com/shaoxiongji/awesome-knowledge-graph
공식 코드A Survey on Knowledge Graphs: Representation, Acquisition and Applications
https://github.com/slerman12/ExplainingInteractions
공식 코드Explaining Local, Global, And Higher-Order Interactions In Deep Learning
https://github.com/sluxsr/r5_graph_reasoning
공식 코드R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning
https://github.com/snap-stanford/csr
공식 코드Few-shot Relational Reasoning via Connection Subgraph Pretraining
https://github.com/stanfordnlp/phrasenode
공식 코드https://github.com/suamin/LowFER
공식 코드https://github.com/taewonpark/DAM
공식 코드Distributed Associative Memory Network with Memory Refreshing Loss
https://github.com/thaihungle/SAM
공식 코드https://github.com/thunlp-mt/vat
공식 코드https://github.com/thunlp/ERICA
공식 코드https://github.com/trangptm/Column_networks
공식 코드https://github.com/tri-gnn/tri-gnn
공식 코드https://github.com/ttrouill/complex
공식 코드https://github.com/ttrouill/induction_experiments
공식 코드On Inductive Abilities of Latent Factor Models for Relational Learning
https://github.com/uclnlp/ctp
공식 코드Learning Reasoning Strategies in End-to-End Differentiable Proving
https://github.com/uestc-gqj/tkre
공식 코드https://github.com/weber-geoml/hypergraph_encodings
공식 코드Enhancing the Utility of Higher-Order Information in Relational Learning
https://github.com/willprice/play-fair
공식 코드https://github.com/wtong98/mlp-icl
공식 코드MLPs Learn In-Context on Regression and Classification Tasks
https://github.com/xingbowen714/darer
공식 코드https://github.com/xwhan/One-shot-Relational-Learning
공식 코드https://github.com/xyfyyds/regrap
공식 코드ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision Assistant
https://github.com/yangliu9208/cmcir
공식 코드Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering
https://github.com/yangliu9208/vcsr
공식 코드https://github.com/yanivbenny/MRNet
공식 코드https://github.com/yanivbenny/RAVEN_FAIR
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.