SOTAVerified

Representation Learning

Representation Learning is a process in machine learning where algorithms extract meaningful patterns from raw data to create representations that are easier to understand and process. These representations can be designed for interpretability, reveal hidden features, or be used for transfer learning. They are valuable across many fundamental machine learning tasks like image classification and retrieval.

Deep neural networks can be considered representation learning models that typically encode information which is projected into a different subspace. These representations are then usually passed on to a linear classifier to, for instance, train a classifier.

Representation learning can be divided into:

  • Supervised representation learning: learning representations on task A using annotated data and used to solve task B
  • Unsupervised representation learning: learning representations on a task in an unsupervised way (label-free data). These are then used to address downstream tasks and reducing the need for annotated data when learning news tasks. Powerful models like GPT and BERT leverage unsupervised representation learning to tackle language tasks.

More recently, self-supervised learning (SSL) is one of the main drivers behind unsupervised representation learning in fields like computer vision and NLP.

Here are some additional readings to go deeper on the task:

( Image credit: Visualizing and Understanding Convolutional Networks )

Papers

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Showing 7601–7650 of 10580 papers

TitleStatusHype
Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting—0
Rapid detection of rare events from in situ X-ray diffraction data using machine learning—0
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning—0
Hierarchically Clustered Representation Learning—0
RAU: Towards Regularized Alignment and Uniformity for Representation Learning in Recommendation—0
Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation—0
RAW-GNN: RAndom Walk Aggregation based Graph Neural Network—0
RAZE: Region Guided Self-Supervised Gaze Representation Learning—0
RBPB: Regularization-Based Pattern Balancing Method for Event Extraction—0
Bidirectional Hierarchical Protein Multi-Modal Representation Learning—0
Representation Learning Beyond Linear Prediction Functions—0
Reachability Embeddings: Scalable Self-Supervised Representation Learning from Mobility Trajectories for Multimodal Geospatial Computer Vision—0
Generalized Category Discovery with Clustering Assignment Consistency—0
DeepCell: Multiview Representation Learning for Post-Mapping Netlists—0
An empirical investigation of neural methods for content scoring of science explanations—0
Representation Learning by Ranking under multiple tasks—0
MDL-Pool: Adaptive Multilevel Graph Pooling Based on Minimum Description Length—0
Deep causal representation learning for unsupervised domain adaptation—0
Hierarchical Disentangle Network for Object Representation Learning—0
Bi-DCSpell: A Bi-directional Detector-Corrector Interactive Framework for Chinese Spelling Check—0
Representation Learning: A Statistical Perspective—0
Hierarchical Disentangled Representation Learning for Outdoor Illumination Estimation and Editing—0
Hierarchical disentangled representation learning for singing voice conversion—0
Hierarchical discriminative learning improves visual representations of biomedical microscopy—0
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings—0
Real-world Person Re-Identification via Degradation Invariance Learning—0
Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition—0
Reasoning over Entity-Action-Location Graph for Procedural Text Understanding—0
An efficient supervised dictionary learning method for audio signal recognition—0
Reasoning Over Semantic-Level Graph for Fact Checking—0
Advances in Protein Representation Learning: Methods, Applications, and Future Directions—0
Representation Learning based and Interpretable Reactor System Diagnosis Using Denoising Padded Autoencoder—0
Representation Learning by Reconstructing Neighborhoods—0
Hierarchical Correlation Clustering and Tree Preserving Embedding—0
Deep auxiliary learning for visual localization using colorization task—0
Hierarchical Convolutional Attention Networks for Text Classification—0
Representation, Learning and Reasoning on Spatial Language for Downstream NLP Tasks—0
Hierarchical Contextual Manifold Alignment for Structuring Latent Representations in Large Language Models—0
Recognize Actions by Disentangling Components of Dynamics—0
Recommendations by Concise User Profiles from Review Text—0
Beyond the Kolmogorov Barrier: A Learnable Weighted Hybrid Autoencoder for Model Order Reduction—0
Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches—0
Hierarchical Context Alignment with Disentangled Geometric and Temporal Modeling for Semantic Occupancy Prediction—0
Reconstruction for disentanglement, Contrast for invariance—0
Reconstruction for Powerful Graph Representations—0
Reconstruction of Hidden Representation for Robust Feature Extraction—0
Hierarchical Conditional End-to-End ASR with CTC and Multi-Granular Subword Units—0
Representation, learning, and planning algorithms for geometric task and motion planning—0
Representation Learning and Recovery in the ReLU Model—0
Hierarchical Compact Clustering Attention (COCA) for Unsupervised Object-Centric Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SciNCLAvg.81.8—Unverified
2SPECTERAvg.80—Unverified
3CiteomaticAvg.76—Unverified
4Sci-DeCLUTRAvg.66.6—Unverified
5SciBERTAvg.59.6—Unverified
6BioBERTAvg.58.8—Unverified
7CiteBERTAvg.58.8—Unverified
#ModelMetricClaimedVerifiedStatus
1top_model_weights_with_3d_21:1 Accuracy0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet 18Accuracy (%)97.05—Unverified
#ModelMetricClaimedVerifiedStatus
1Morphological NetworkAccuracy97.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Max Margin ContrastiveSilhouette Score0.56—Unverified