Papers with Code 아카이브
MULTI-VIEW LEARNING
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Multi-View Learning is a machine learning framework where data are represented by multiple distinct feature groups, and each feature group is referred to as a particular view.
Source: Dissimilarity-based representation for radiomics applications
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Leo02016/DeepMTMV
https://github.com/MindCode-4/code-10/tree/main/BLS
Multi-View Broad Learning System for Primate Oculomotor Decision Decoding
https://github.com/MiuGod0126/TMC_Paddle
https://github.com/PaddlePaddle/PaddleRec/tree/master/models/rank/naml
Neural News Recommendation with Attentive Multi-View Learning
https://github.com/Rec4Fun/BunCa_ECMLPKDD_24
Bundle Recommendation with Item-level Causation-enhanced Multi-view Learning
https://github.com/XLearning-SCU/2021-CVPR-Completer
https://github.com/XLearning-SCU/2022-TPAMI-DCP
https://github.com/basiralab/MV-LEAP
Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction
https://github.com/code-implementation1/Code5/tree/main/MVD
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
https://github.com/dmcv-ecnu/MindSpore_ModelZoo/tree/main/MVD
https://github.com/dscv-lab/KMF2JMTtracking
Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling
https://github.com/go0day/lm4newsrec
Neural News Recommendation with Attentive Multi-View Learning
https://github.com/hanmenghan/CPM_Nets
https://github.com/hdcouture/TOCCA
https://github.com/jameschapman19/cca_zoo
Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction
https://github.com/kjf4096/TMC
https://github.com/ldmt-muri/alignment-with-openfst
Conditional Random Field Autoencoders for Unsupervised Structured Prediction
https://github.com/luxusg1/metabu
https://github.com/markWJJ/Multitask-Learning
https://github.com/mindspore-ai/models/tree/master/official/recommend/naml
Neural News Recommendation with Attentive Multi-View Learning
https://github.com/mindspore-ai/models/tree/master/research/cv/MVD
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
https://github.com/pwc-1/Paper-9/tree/main/6/MVD
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
https://github.com/rciszek/mdr_tcca
Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction
https://github.com/uakarsh/Eit-Enhanced-Interactive-Transformer
https://github.com/wrlife/RNN_depth_pose
Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and Depth
https://github.com/yusanshi/NewsRecommendation
Neural News Recommendation with Attentive Multi-View Learning
https://github.com/yusanshi/news-recommendation
Neural News Recommendation with Attentive Multi-View Learning
https://github.com/zhangzw12319/MVD
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.