Papers with Code 아카이브

MULTI-VIEW LEARNING

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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/himashi92/Duo-SegNet

공식 코드

Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation

https://github.com/hugorichard/shica

공식 코드

Shared Independent Component Analysis for Multi-Subject Neuroimaging

https://github.com/jameschapman19/gep-ey

공식 코드

Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning

https://github.com/jameschapman19/ssl-ey

공식 코드

Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning

https://github.com/jiajunsi/rcml

공식 코드

Reliable Conflictive Multi-View Learning

https://github.com/joseangl/transience

공식 코드

Multi-view Temporal Alignment for Non-parallel Articulatory-to-Acoustic Speech Synthesis

https://github.com/justsmart/LSIMVC

공식 코드

Localized Sparse Incomplete Multi-view Clustering

https://github.com/justsmart/RecFormer

공식 코드

Information Recovery-Driven Deep Incomplete Multiview Clustering Network

https://github.com/justsmart/Recformer-mindspore

공식 코드

Information Recovery-Driven Deep Incomplete Multiview Clustering Network

https://github.com/kdegroup/cmt

공식 코드

Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph

https://github.com/li-z-q/url

공식 코드

URL: Universal Referential Knowledge Linking via Task-instructed Representation Compression

https://github.com/libertyhhn/PartiallySharedDMF

공식 코드

Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view Data

https://github.com/lihong-liu/ccml

공식 코드

Dynamic Evidence Decoupling for Trusted Multi-view Learning

https://github.com/liunian-jay/icmvc

공식 코드

Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding

https://github.com/lshi91/GTMC-HOA

공식 코드

Generalized Trusted Multi-view Classification Framework with Hierarchical Opinion Aggregation

https://github.com/megvii-research/co-mining

공식 코드

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

https://github.com/memexproject/memex-kg

공식 코드

Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding

https://github.com/microsoft/recommenders

공식 코드

Neural News Recommendation with Attentive Multi-View Learning

https://github.com/reagan0323/iRRR

공식 코드

Integrative Multi-View Reduced-Rank Regression: Bridging Group-Sparse and Low-Rank Models

https://github.com/scientific-computing-lab-nrcn/multi-view-explainability

공식 코드

Explainable Multi-View Deep Networks Methodology for Experimental Physics

https://github.com/seeker98/crwkv

공식 코드

Multi-View Learning with Context-Guided Receptance for Image Denoising

https://github.com/shaham-lab/specrage

공식 코드

Generalizable and Robust Spectral Method for Multi-view Representation Learning

https://github.com/thaihungle/DMNC

공식 코드

Dual Memory Neural Computer for Asynchronous Two-view Sequential Learning

https://github.com/tu-rbo/concarne

공식 코드

Patterns for Learning with Side Information

https://github.com/weilvnju/jpltd

공식 코드

Joint Projection Learning and Tensor Decomposition Based Incomplete Multi-view Clustering

https://github.com/wy1019/simvc-sa

공식 코드

Scalable Incomplete Multi-View Clustering with Structure Alignment

https://github.com/yaoyueduzhen/DADA

공식 코드

Dual Adversarial Domain Adaptation

https://github.com/yashpatel5400/fusioncp

공식 코드

Conformal Prediction for Ensembles: Improving Efficiency via Score-Based Aggregation

https://github.com/yyaghoobzadeh/MVET

공식 코드

Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing

https://github.com/zachstarkk/asm2tv

공식 코드

ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity Recognition

https://github.com/zehong-wang/hgcml

공식 코드

Heterogeneous Graph Contrastive Multi-view Learning

https://github.com/zhengkid/eit-enhanced-interactive-transformer

공식 코드

EIT: Enhanced Interactive Transformer

https://github.com/zhouchunpong/multi-view-3DGPR

공식 코드

Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR

https://github.com/zx55/siamesedetr

공식 코드

https://github.com/2023-MindSpore-1/ms-code-220/tree/main/naml

Neural News Recommendation with Attentive Multi-View Learning

https://github.com/2023-MindSpore-4/Code13/tree/main/zhangchangqing/MpTMC-main

Trusted Multi-View Classification with Dynamic Evidential Fusion

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