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 5101–5150 of 10580 papers

TitleStatusHype
Investigating Speaker Embedding Disentanglement on Natural Read Speech—0
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data—0
Video-based Person Re-identification with Long Short-Term Representation Learning—0
Local Structure-aware Graph Contrastive Representation Learning—0
MOMA-Force: Visual-Force Imitation for Real-World Mobile Manipulation—0
Imbalanced Large Graph Learning Framework for FPGA Logic Elements Packing Prediction—0
Biomedical Knowledge Graph Embeddings with Negative StatementsCode0
Deep Feature Learning for Wireless Spectrum Data—0
Semantic-Guided Feature Distillation for Multimodal RecommendationCode0
Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables—0
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
DiffDance: Cascaded Human Motion Diffusion Model for Dance Generation—0
Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching—0
Model Provenance via Model DNA—0
Event-based Dynamic Graph Representation Learning for Patent Application Trend PredictionCode0
DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization—0
Federated Representation Learning for Automatic Speech Recognition—0
Disentangling Multi-view Representations Beyond Inductive BiasCode0
Unsupervised Multiplex Graph Learning with Complementary and Consistent InformationCode0
ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction PredictionCode0
Factor Graph Neural Networks—0
Graph Contrastive Learning with Generative Adversarial Network—0
Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding—0
Contrastive Conditional Latent Diffusion for Audio-visual SegmentationCode0
Relation-Oriented: Toward Causal Knowledge-Aligned AGI—0
C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation—0
Can Self-Supervised Representation Learning Methods Withstand Distribution Shifts and Corruptions?Code0
InfoStyler: Disentanglement Information Bottleneck for Artistic Style Transfer—0
Graph Condensation for Inductive Node Representation Learning—0
MUSE: Multi-View Contrastive Learning for Heterophilic Graphs—0
UniBriVL: Robust Universal Representation and Generation of Audio Driven Diffusion Models—0
HandMIM: Pose-Aware Self-Supervised Learning for 3D Hand Mesh Estimation—0
Point Clouds Are Specialized Images: A Knowledge Transfer Approach for 3D Understanding—0
Aligned Unsupervised Pretraining of Object Detectors with Self-training—0
Distillation-guided Representation Learning for Unconstrained Gait Recognition—0
Gradient-Based Spectral Embeddings of Random Dot Product GraphsCode0
Neural Memory Decoding with EEG Data and Representation Learning—0
Speech representation learning: Learning bidirectional encoders with single-view, multi-view, and multi-task methods—0
Compact & Capable: Harnessing Graph Neural Networks and Edge Convolution for Medical Image Classification—0
How Does Naming Affect LLMs on Code Analysis Tasks?—0
Phase Matching for Out-of-Distribution Generalization—0
DEPHN: Different Expression Parallel Heterogeneous Network using virtual gradient optimization for Multi-task Learning—0
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network—0
Nonparametric Linear Feature Learning in Regression Through RegularisationCode0
Balancing Exploration and Exploitation in Hierarchical Reinforcement Learning via Latent Landmark GraphsCode0
Hallucination Improves the Performance of Unsupervised Visual Representation Learning—0
Learning minimal representations of stochastic processes with variational autoencodersCode0
DEFTri: A Few-Shot Label Fused Contextual Representation Learning For Product Defect Triage in e-Commerce—0
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs—0
Learning Discriminative Visual-Text Representation for Polyp Re-IdentificationCode0
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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