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MULTI-VIEW LEARNING

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

Papers

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Showing 1–50 of 256 papers

TitleStatusHype
Trusted Multi-View Classification with Dynamic Evidential FusionCode2
Reliable Conflictive Multi-View LearningCode2
Deep Multi-View Learning via Task-Optimal CCACode1
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
A Clustering-guided Contrastive Fusion for Multi-view Representation LearningCode1
COMPLETER: Incomplete Multi-view Clustering via Contrastive PredictionCode1
Tensor Canonical Correlation Analysis for Multi-view Dimension ReductionCode1
Multi-View Learning with Context-Guided Receptance for Image DenoisingCode1
Localized Sparse Incomplete Multi-view ClusteringCode1
Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing ApplicationsCode1
Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPRCode1
Siamese DETRCode1
Deep Tensor CCA for Multi-view LearningCode1
CPM-Nets: Cross Partial Multi-View NetworksCode1
A Comparative Assessment of Multi-view fusion learning for Crop ClassificationCode1
Heterogeneous Graph Contrastive Multi-view LearningCode1
Shared Independent Component Analysis for Multi-Subject NeuroimagingCode1
SleepPoseNet: Multi-View Learning for Sleep Postural Transition Recognition Using UWBCode1
TSCMamba: Mamba Meets Multi-View Learning for Time Series ClassificationCode1
Variational Distillation for Multi-View LearningCode1
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-IdentificationCode1
Co-mining: Self-Supervised Learning for Sparsely Annotated Object DetectionCode1
Trusted Multi-View ClassificationCode1
Dual Contrastive Prediction for Incomplete Multi-view Representation LearningCode1
Dual Adversarial Domain AdaptationCode1
Learning Autoencoders with Relational RegularizationCode1
LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal DataCode1
Robust Variational Contrastive Learning for Partially View-unaligned ClusteringCode1
Molecule Generation for Target Protein Binding with Hierarchical Consistency Diffusion ModelCode1
ConsRec: Learning Consensus Behind Interactions for Group RecommendationCode1
A Survey on Multi-Task LearningCode0
Multi-Multi-View Learning: Multilingual and Multi-Representation Entity TypingCode0
ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity RecognitionCode0
Missing Data as Augmentation in the Earth Observation Domain: A Multi-View Learning ApproachCode0
Multi-View Broad Learning System for Primate Oculomotor Decision DecodingCode0
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing DataCode0
Learning Dual Retrieval Module for Semi-supervised Relation ExtractionCode0
Impact Assessment of Missing Data in Model Predictions for Earth Observation ApplicationsCode0
Increasing the Robustness of Model Predictions to Missing Sensors in Earth ObservationCode0
Integrative Multi-View Reduced-Rank Regression: Bridging Group-Sparse and Low-Rank ModelsCode0
Ensemble of Multi-View Learning Classifiers for Cross-Domain Iris Presentation Attack DetectionCode0
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised LearningCode0
Bundle Recommendation with Item-level Causation-enhanced Multi-view LearningCode0
EIT: Enhanced Interactive TransformerCode0
Generalized Trusted Multi-view Classification Framework with Hierarchical Opinion AggregationCode0
Explainable Multi-View Deep Networks Methodology for Experimental PhysicsCode0
Dual Memory Neural Computer for Asynchronous Two-view Sequential LearningCode0
Balanced Multi-view ClusteringCode0
Adaptive Fusion of Multi-view Remote Sensing data for Optimal Sub-field Crop Yield PredictionCode0
Dynamic Evidence Decoupling for Trusted Multi-view LearningCode0
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