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 4051–4100 of 10580 papers

TitleStatusHype
ImpDet: Exploring Implicit Fields for 3D Object Detection—0
Implications of sparsity and high triangle density for graph representation learning—0
A Deep Representation Learning-based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencoder—0
Graph Learning and Its Advancements on Large Language Models: A Holistic Survey—0
Graph Learning with Localized Neighborhood Fairness—0
Improved Representation Learning for Question Answer Matching—0
Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality—0
Graph-Level Embedding for Time-Evolving Graphs—0
Imbalanced Large Graph Learning Framework for FPGA Logic Elements Packing Prediction—0
Efficient Feature Representations for Cricket Data Analysis using Deep Learning based Multi-Modal Fusion Model—0
Agent-Centric Representations for Multi-Agent Reinforcement Learning—0
IMB-NAS: Neural Architecture Search for Imbalanced Datasets—0
Efficient Fairness-Performance Pareto Front Computation—0
Academic Network Representation via Prediction-Sampling Incorporated Tensor Factorization—0
Sparse-Dyn: Sparse Dynamic Graph Multi-representation Learning via Event-based Sparse Temporal Attention Network—0
A Survey of Multi-View Representation Learning—0
Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations—0
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax—0
Efficient Deep Representation Learning by Adaptive Latent Space Sampling—0
Graph Neural Network Based VC Investment Success Prediction—0
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning—0
Efficient Policy Generation in Multi-Agent Systems via Hypergraph Neural Network—0
Graph Neural Networks for Binary Programming—0
Efficient Contextual Representation Learning With Continuous Outputs—0
CO2: Consistent Contrast for Unsupervised Visual Representation Learning—0
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization—0
Graph Neural Networks Including Sparse Interpretability—0
Efficient Contextual Representation Learning Without Softmax Layer—0
CNNTOP: a CNN-based Trajectory Owner Prediction Method—0
Efficient Communication via Self-supervised Information Aggregation for Online and Offline Multi-agent Reinforcement Learning—0
Efficient Codebook and Factorization for Second Order Representation Learning—0
Graph Neural Networks with Feature and Structure Aware Random Walk—0
Feature Interaction-aware Graph Neural Networks—0
Cyclic Refiner: Object-Aware Temporal Representation Learning for Multi-View 3D Detection and Tracking—0
CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse—0
A Survey of Learning on Small Data: Generalization, Optimization, and Challenge—0
A generic self-supervised learning (SSL) framework for representation learning from spectra-spatial feature of unlabeled remote sensing imagery—0
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making—0
CNN based Multi-Instance Multi-Task Learning for Syndrome Differentiation of Diabetic Patients—0
Graph Ordering: Towards the Optimal by Learning—0
Graph Partial Label Learning with Potential Cause Discovering—0
Graph Persistence goes Spectral—0
GraphPMU: Event Clustering via Graph Representation Learning Using Locationally-Scarce Distribution-Level Fundamental and Harmonic PMU Measurements—0
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning—0
CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data—0
Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation—0
Image Retrieval with Intra-Sweep Representation Learning for Neck Ultrasound Scanning Guidance—0
CN-Motifs Perceptive Graph Neural Networks—0
Efficiency-oriented approaches for self-supervised speech representation learning—0
A Survey of Knowledge Enhanced Pre-trained 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