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 6651–6700 of 10580 papers

TitleStatusHype
Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages—0
Multi-Augmentation for Efficient Visual Representation Learning for Self-supervised Pre-trainingCode0
Emergent Communication through Metropolis-Hastings Naming Game with Deep Generative ModelsCode0
SCVRL: Shuffled Contrastive Video Representation Learning—0
Associative Learning Mechanism for Drug-Target Interaction Prediction—0
Phased Progressive Learning with Coupling-Regulation-Imbalance Loss for Imbalanced Data Classification—0
Learning multi-scale functional representations of proteins from single-cell microscopy data—0
Online Hybrid Lightweight Representations Learning: Its Application to Visual Tracking—0
Contrastive Representation Learning for Cross-Document Coreference Resolution of Events and Entities—0
Conditional Supervised Contrastive Learning for Fair Text ClassificationCode0
UnifieR: A Unified Retriever for Large-Scale Retrieval—0
Revisiting the role of heterophily in graph representation learning: An edge classification perspective—0
Causal Machine Learning for Healthcare and Precision Medicine—0
KQGC: Knowledge Graph Embedding with Smoothing Effects of Graph Convolutions for Recommendation—0
Self-Supervised Speech Representation Learning: A Review—0
Improvements to Self-Supervised Representation Learning for Masked Image Modeling—0
Tackling Provably Hard Representative Selection via Graph Neural Networks—0
Data Augmentation for Compositional Data: Advancing Predictive Models of the MicrobiomeCode0
A Unified Collaborative Representation Learning for Neural-Network based Recommender Systems—0
AIGenC: An AI generalisation model via creativity—0
Are Graph Representation Learning Methods Robust to Graph Sparsity and Asymmetric Node Information?—0
Improving Multi-Task Generalization via Regularizing Spurious Correlation—0
Image Augmentation Based Momentum Memory Intrinsic Reward for Sparse Reward Visual Scenes—0
Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modeling—0
Practical Skills Demand Forecasting via Representation Learning of Temporal Dynamics—0
Learning latent representations for operational nitrogen response rate prediction—0
Relational representation learning with spike trains—0
SAMU-XLSR: Semantically-Aligned Multimodal Utterance-level Cross-Lingual Speech Representation—0
A two-steps approach to improve the performance of Android malware detectors—0
Self-Supervised Learning of Multi-Object Keypoints for Robotic Manipulation—0
Monotonicity Regularization: Improved Penalties and Novel Applications to Disentangled Representation Learning and Robust Classification—0
KGNN: Distributed Framework for Graph Neural Knowledge Representation—0
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibilityCode0
Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation—0
Clinical outcome prediction under hypothetical interventions -- a representation learning framework for counterfactual reasoning—0
Real-centric Consistency Learning for Deepfake Detection—0
Voxel-wise Adversarial Semi-supervised Learning for Medical Image Segmentation—0
BronchusNet: Region and Structure Prior Embedded Representation Learning for Bronchus Segmentation and Classification—0
Representation learning with function call graph transformations for malware open set recognition—0
Embodied-Symbolic Contrastive Graph Self-Supervised Learning for Molecular Graphs—0
Unsupervised Representation Learning for 3D MRI Super Resolution with Degradation Adaptation—0
Accounting for the Sequential Nature of States to Learn Features for Reinforcement Learning—0
Unsupervised Driving Behavior Analysis using Representation Learning and Exploiting Group-based Training—0
Representation Learning for Context-Dependent Decision-Making—0
kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval—0
Visuomotor Control in Multi-Object Scenes Using Object-Aware Representations—0
A deep representation learning speech enhancement method using β-VAE—0
Hyperspectral Image Classification With Contrastive Graph Convolutional NetworkCode0
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training—0
CoDo: Contrastive Learning with Downstream Background Invariance for Detection—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