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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 10151–10200 of 10580 papers

TitleStatusHype
Generalized Category Discovery with Clustering Assignment Consistency—0
Rapid detection of rare events from in situ X-ray diffraction data using machine learning—0
Rare Event Detection using Disentangled Representation Learning—0
Generalized Information Bottleneck for Gaussian Variables—0
Generalized Laplacian Positional Encoding for Graph Representation Learning—0
RAU: Towards Regularized Alignment and Uniformity for Representation Learning in Recommendation—0
Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environments—0
Out-of-Distribution Representation Learning for Time Series Classification—0
Generalized User Representations for Transfer Learning—0
RAW-GNN: RAndom Walk Aggregation based Graph Neural Network—0
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs—0
Generalizing Reinforcement Learning to Unseen Actions—0
Generalizing Supervised Contrastive learning: A Projection Perspective—0
Generalizing to Unseen Domains: A Survey on Domain Generalization—0
RAZE: Region Guided Self-Supervised Gaze Representation Learning—0
RBPB: Regularization-Based Pattern Balancing Method for Event Extraction—0
General-purpose audio representation learning for real-world sound scenes—0
General-Purpose Speech Representation Learning through a Self-Supervised Multi-Granularity Framework—0
Self-Supervised Learning of Domain Invariant Features for Depth Estimation—0
Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning—0
Generating Drug Repurposing Hypotheses through the Combination of Disease-Specific Hypergraphs—0
Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models—0
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness—0
Generating Privacy-Preserving Process Data with Deep Generative Models—0
Generating the Graph Gestalt: Kernel-Regularized Graph Representation Learning—0
Generating Videos with Scene Dynamics—0
Generative Adversarial Image Synthesis with Decision Tree Latent Controller—0
Generative Adversarial Networks for Multimodal Representation Learning in Video Hyperlinking—0
Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories—0
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm—0
Reachability Embeddings: Scalable Self-Supervised Representation Learning from Mobility Trajectories for Multimodal Geospatial Computer Vision—0
Generative Modeling for Atmospheric Convection—0
Generative Modeling of Class Probability for Multi-Modal Representation Learning—0
Generative or Contrastive? Phrase Reconstruction for Better Sentence Representation Learning—0
Generative Pretraining for Paraphrase Evaluation—0
Generative Pretraining for Paraphrase Evaluation—0
Semantic Graph Consistency: Going Beyond Patches for Regularizing Self-Supervised Vision Transformers—0
A Computational Model of Representation Learning in the Brain Cortex, Integrating Unsupervised and Reinforcement Learning—0
Generative Slate Recommendation with Reinforcement Learning—0
Semantic Graph Representation Learning for Handwritten Mathematical Expression Recognition—0
README: REpresentation learning by fairness-Aware Disentangling MEthod—0
Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentation—0
Generative View-Correlation Adaptation for Semi-Supervised Multi-View Learning—0
Generic Multi-modal Representation Learning for Network Traffic Analysis—0
Generic Multimodal Spatially Graph Network for Spatially Embedded Network Representation Learning—0
Real-centric Consistency Learning for Deepfake Detection—0
Real Face Foundation Representation Learning for Generalized Deepfake Detection—0
Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies—0
GENIUS: A Novel Solution for Subteam Replacement with Clustering-based Graph Neural Network—0
GEN Model: An Alternative Approach to Deep Neural Network Models—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