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 8401–8450 of 10580 papers

TitleStatusHype
DAS-MAE: A self-supervised pre-training framework for universal and high-performance representation learning of distributed fiber-optic acoustic sensing—0
Self-Supervised Learning for Medical Image Data with Anatomy-Oriented Imaging Planes—0
BERTERS: Multimodal Representation Learning for Expert Recommendation System with Transformer—0
An analysis on the effects of speaker embedding choice in non auto-regressive TTS—0
Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train—0
ScaleNet: An Unsupervised Representation Learning Method for Limited Information—0
DARI: Distance metric And Representation Integration for Person Verification—0
Self-supervised Learning for Unintentional Action Prediction—0
Guiding Representation Learning in Deep Generative Models with Policy Gradients—0
Self-Supervised Radio-Visual Representation Learning for 6G Sensing—0
Self-supervised Learning: Generative or Contrastive—0
Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment—0
SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition—0
Graph Reinforcement Learning for Power Grids: A Comprehensive Survey—0
Scalable Variational Quantum Circuits for Autoencoder-based Drug Discovery—0
Scalable Semi-Supervised Query Classification Using Matrix Sketching—0
Graph Regularized Nonnegative Tensor Ring Decomposition for Multiway Representation Learning—0
Self-Supervised Ranking for Representation Learning—0
Self-Supervised Learning of Multi-Object Keypoints for Robotic Manipulation—0
Learning Music-Dance Representations through Explicit-Implicit Rhythm Synchronization—0
Self-Supervised Representation Learning: Introduction, Advances and Challenges—0
Scalable Self-Supervised Representation Learning from Spatiotemporal Motion Trajectories for Multimodal Computer Vision—0
Graph Regularized and Feature Aware Matrix Factorization for Robust Incomplete Multi-view Clustering—0
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees—0
Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models—0
Scalable Representation Learning for Multimodal Tabular Transactions—0
Self-Supervised Learning Using Nonlinear Dependence—0
Self-Supervised Learning via multi-Transformation Classification for Action Recognition—0
Self-supervised learning with bi-label masked speech prediction for streaming multi-talker speech recognition—0
Review-Based Domain Disentanglement without Duplicate Users or Contexts for Cross-Domain Recommendation—0
DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains—0
A Named Entity Recognition Shootout for German—0
Scalable Pathogen Detection from Next Generation DNA Sequencing with Deep Learning—0
Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks—0
Self-Supervised Pretraining of Graph Neural Network for the Retrieval of Related Mathematical Expressions in Scientific Articles—0
Self-Supervised Pretraining on Satellite Imagery: a Case Study on Label-Efficient Vehicle Detection—0
Scalable Numerical Embeddings for Multivariate Time Series: Enhancing Healthcare Data Representation Learning—0
Self-supervised Multimodal Speech Representations for the Assessment of Schizophrenia Symptoms—0
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning—0
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations—0
Scalable Multitask Representation Learning for Scene Classification—0
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs—0
3D Hand Pose Estimation via Regularized Graph Representation Learning—0
DALG: Deep Attentive Local and Global Modeling for Image Retrieval—0
Graph Pooling with Node Proximity for Hierarchical Representation Learning—0
Rumour Detection via News Propagation Dynamics and User Representation Learning—0
Scalable Hierarchical Embeddings of Complex Networks—0
Self-supervised Pre-training with Hard Examples Improves Visual Representations—0
Representation Uncertainty in Self-Supervised Learning as Variational Inference—0
Self-Supervised Representation Learning From Multi-Domain Data—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