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 8551–8600 of 10580 papers

TitleStatusHype
EEMC: Embedding Enhanced Multi-tag Classification—0
Zero-Shot Clinical Acronym Expansion via Latent Meaning CellsCode0
Selective Cascade of Residual ExtraTrees—0
Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders—0
Cross-Task Representation Learning for Anatomical Landmark Detection—0
Factorized linear discriminant analysis for phenotype-guided representation learning of neuronal gene expression data—0
What About Taking Policy as Input of Value Function: Policy-extended Value Function Approximator—0
Mixture Representation Learning with Coupled Autoencoding Agents—0
Learning Online Data Association—0
Deep Clustering and Representation Learning that Preserves Geometric Structures—0
Multi-timescale Representation Learning in LSTM Language Models—0
VATLD: A Visual Analytics System to Assess, Understand and Improve Traffic Light Detection—0
Unsupervised Pre-training for Biomedical Question Answering—0
Piece-wise Matching Layer in Representation Learning for ECG Classification—0
AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding—0
Learning Representations of Hierarchical Slates in Collaborative Filtering—0
Learning Sparse Sentence Encoding without Supervision: An Exploration of Sparsity in Variational AutoencodersCode0
Deep Adversarial Transition Learning using Cross-Grafted Generative Stacks—0
Scalable Recommendation of Wikipedia Articles to Editors Using Representation LearningCode0
Towards a Flexible Embedding Learning Framework—0
HiCOMEX: Facial Action Unit Recognition Based on Hierarchy Intensity Distribution and COMEX Relation Learning—0
Unsupervised Feature Learning for Event Data: Direct vs Inverse Problem Formulation—0
Evolutionary Architecture Search for Graph Neural NetworksCode0
div2vec: Diversity-Emphasized Node Embedding—0
Improving Robustness and Generality of NLP Models Using Disentangled Representations—0
Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders—0
Chemical Property Prediction Under Experimental Biases—0
Learning to Identify Physical Parameters from Video Using Differentiable Physics—0
Layer-stacked Attention for Heterogeneous Network Embedding—0
AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent LossCode0
Self-supervised pre-training and contrastive representation learning for multiple-choice video QA—0
Job2Vec: Job Title Benchmarking with Collective Multi-View Representation Learning—0
Polyp-artifact relationship analysis using graph inductive learned representations—0
Matching in Selective and Balanced Representation Space for Treatment Effects Estimation—0
DynamicVAE: Decoupling Reconstruction Error and Disentangled Representation Learning—0
Adaptive Text Recognition through Visual Matching—0
Accelerating Graph Sampling for Graph Machine Learning using GPUs—0
Collaborative Attention Mechanism for Multi-View Action Recognition—0
SA-Net: A deep spectral analysis network for image clustering—0
Spectral Analysis Network for Deep Representation Learning and Image Clustering—0
An unsupervised deep learning framework via integrated optimization of representation learning and GMM-based modeling—0
GTEA: Inductive Representation Learning on Temporal Interaction Graphs via Temporal Edge AggregationCode0
Learning Universal Representations from Word to Sentence—0
Learning Behavioral Representations of Human Mobility—0
Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior—0
Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks—0
Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction—0
Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation—0
Don't miss the Mismatch: Investigating the Objective Function Mismatch for Unsupervised Representation LearningCode0
About Graph Degeneracy, Representation Learning and ScalabilityCode0
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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
6CiteBERTAvg.58.8—Unverified
7BioBERTAvg.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