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 4701–4750 of 10580 papers

TitleStatusHype
Cross-view Topology Based Consistent and Complementary Information for Deep Multi-view Clustering—0
Cross-View-Prediction: Exploring Contrastive Feature for Hyperspectral Image Classification—0
Graph Condensation for Inductive Node Representation Learning—0
On Understanding and Mitigating the Dimensional Collapse of Graph Contrastive Learning: a Non-Maximum Removal Approach—0
Cross view link prediction by learning noise-resilient representation consensus—0
BCDR: Betweenness Centrality-based Distance Resampling for Graph Shortest Distance Embedding—0
GraphCL-DTA: a graph contrastive learning with molecular semantics for drug-target binding affinity prediction—0
GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning—0
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models—0
Graph Anomaly Detection in Time Series: A Survey—0
Cross-view Graph Contrastive Representation Learning on Partially Aligned Multi-view Data—0
Graph-Based Re-ranking: Emerging Techniques, Limitations, and Opportunities—0
Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks—0
CrossVideoMAE: Contrastive Spatiotemporal and Semantic Representation Learning from Videos and Images with Masked Autoencoders—0
An algebraic theory to discriminate qualia in the brain—0
A Deep Paradigm for Articulatory Speech Representation Learning via Neural Convolutive Sparse Matrix Factorization—0
Graph-based Isometry Invariant Representation Learning—0
Cross-Training with Multi-View Knowledge Fusion for Heterogenous Federated Learning—0
Graph-Based Generative Representation Learning of Semantically and Behaviorally Augmented Floorplans—0
Cross-Task Representation Learning for Anatomical Landmark Detection—0
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning—0
Graph-based Aspect Representation Learning for Entity Resolution—0
Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks—0
Bayesian representation learning with oracle constraints—0
Graph Attention Collaborative Similarity Embedding for Recommender System—0
Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modeling—0
Graph Anomaly Detection via Adaptive Test-time Representation Learning across Out-of-Distribution Domains—0
Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition—0
Graph AI in Medicine—0
Cross-State Self-Constraint for Feature Generalization in Deep Reinforcement Learning—0
Bayesian Neural Decoding Using A Diversity-Encouraging Latent Representation Learning Method—0
An Adaptive Alternating-direction-method-based Nonnegative Latent Factor Model—0
Graph2Tac: Online Representation Learning of Formal Math Concepts—0
Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation—0
GRAPE: Heterogeneous Graph Representation Learning for Genetic Perturbation with Coding and Non-Coding Biotype—0
Bayesian Models of Functional Connectomics and Behavior—0
Learning from Neighbors: Category Extrapolation for Long-Tail Learning—0
Granular-ball Representation Learning for Deep CNN on Learning with Label Noise—0
GRANDE: a neural model over directed multigraphs with application to anti-money laundering—0
Bayesian Learning of Latent Representations of Language Structures—0
A Mutually Reinforced Framework for Pretrained Sentence Embeddings—0
GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation—0
Cross-Patient Pseudo Bags Generation and Curriculum Contrastive Learning for Imbalanced Multiclassification of Whole Slide Image—0
GraLSP: Graph Neural Networks with Local Structural Patterns—0
GraFT: Gradual Fusion Transformer for Multimodal Re-Identification—0
Cross-Paced Representation Learning with Partial Curricula for Sketch-based Image Retrieval—0
Graffin: Stand for Tails in Imbalanced Node Classification—0
Graffe: Graph Representation Learning via Diffusion Probabilistic Models—0
Gradual Learning of Matrix-Space Models of Language for Sentiment Analysis—0
Bayesian Hierarchical Words Representation 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