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 6301–6350 of 10580 papers

TitleStatusHype
Impact of Strategic Sampling and Supervision Policies on Semi-supervised Learning—0
MVC: A Multi-Task Vision Transformer Network for COVID-19 Diagnosis from Chest X-ray Images—0
Deep Representation Learning and Clustering of Traffic Scenarios—0
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning—0
Motion Sensitive Contrastive Learning for Self-supervised Video Representation—0
MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions—0
Enhance Hyperbolic Representation Learning via Second-order Pooling—0
MPRE: Multi-perspective Patient Representation Extractor for Disease Prediction—0
MPT-PAR:Mix-Parameters Transformer for Panoramic Activity Recognition—0
Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning—0
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making—0
Bootstrap Equilibrium and Probabilistic Speaker Representation Learning for Self-supervised Speaker Verification—0
Deep Reinforcement Learning with Decorrelation—0
IMB-NAS: Neural Architecture Search for Imbalanced Datasets—0
Mutual Information Minimization Based Disentangled Learning Framework For Causal Effect Estimation—0
Imbalanced Large Graph Learning Framework for FPGA Logic Elements Packing Prediction—0
Deep reinforcement learning guided graph neural networks for brain network analysis—0
MSD-LLM: Predicting Ship Detention in Port State Control Inspections with Large Language Model—0
Deep Reinforcement Learning for NLP—0
Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations—0
Imagined Speech State Classification for Robust Brain-Computer Interface—0
Mutual Information Estimation as a Difference of Entropies for Unsupervised Representation Learning—0
Image-Text Multi-Modal Representation Learning by Adversarial Backpropagation—0
Boosting Video Representation Learning with Multi-Faceted Integration—0
MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization—0
MusicTM-Dataset for Joint Representation Learning among Sheet Music, Lyrics, and Musical Audio—0
Image Retrieval with Intra-Sweep Representation Learning for Neck Ultrasound Scanning Guidance—0
Image Representation Learning Using Graph Regularized Auto-Encoders—0
Deep Reinforcement Learning for Autonomous Driving: A Survey—0
An Information Theoretic Approach to Distributed Representation Learning—0
Multi-Agent Actor-Critic with Hierarchical Graph Attention Network—0
Enhancing Dialogue Speech Recognition with Robust Contextual Awareness via Noise Representation Learning—0
Image Generation and Translation with Disentangled Representations—0
Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction—0
Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition—0
Image Compression with Product Quantized Masked Image Modeling—0
Enhancing Edge Intelligence with Highly Discriminant LNT Features—0
Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation—0
Multi-constrained Symmetric Nonnegative Latent Factor Analysis for Accurately Representing Large-scale Undirected Weighted Networks—0
Image-Based Vehicle Classification by Synergizing Features from Supervised and Self-Supervised Learning Paradigms—0
Multi-Dialectal Representation Learning of Sinitic Phonology—0
Deep Ranking for Person Re-identification via Joint Representation Learning—0
Image Augmentation Based Momentum Memory Intrinsic Reward for Sparse Reward Visual Scenes—0
Compact & Capable: Harnessing Graph Neural Networks and Edge Convolution for Medical Image Classification—0
Multi-Domain Causal Representation Learning via Weak Distributional Invariances—0
Multi-Domain Self-Supervised Learning—0
Image Annotation based on Deep Hierarchical Context Networks—0
MultiEarth 2022 -- Multimodal Learning for Earth and Environment Workshop and Challenge—0
Deep Q-Learning with Low Switching Cost—0
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation—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