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 5301–5350 of 10580 papers

TitleStatusHype
Learning Causal Representation for Training Cross-Domain Pose Estimator via Generative Interventions—0
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity—0
Uplifting Message Passing Neural Network with Graph Original Information—0
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks—0
Learning Chemical Reaction Representation with Reactant-Product Alignment—0
Learning Color Representations for Low-Light Image Enhancement—0
Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs—0
Dementia Severity Classification under Small Sample Size and Weak Supervision in Thick Slice MRI—0
Inductive Topic Variational Graph Auto-Encoder for Text Classification—0
Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models—0
Break The Spell Of Total Correlation In betaTCVAE—0
A Non-negative VAE:the Generalized Gamma Belief Network—0
Causal Perception Inspired Representation Learning for Trustworthy Image Quality Assessment—0
A Representation Learning Approach to Animal Biodiversity Conservation—0
Disentangling Properties of Contrastive Methods—0
Learning Controllable Elements Oriented Representations for Reinforcement Learning—0
Learning Co-Speech Gesture Representations in Dialogue through Contrastive Learning: An Intrinsic Evaluation—0
Learning crop type mapping from regional label proportions in large-scale SAR and optical imagery—0
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations—0
Leveraging Herpangina Data to Enhance Hospital-level Prediction of Hand-Foot-and-Mouth Disease Admissions Using UPTST—0
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks—0
Learning Cross-lingual Visual Speech Representations—0
Delineation of line patterns in images using B-COSFIRE filters—0
Learning Decomposable and Debiased Representations via Attribute-Centric Information Bottlenecks—0
Causal Regularization—0
Learning Deep Context-aware Features over Body and Latent Parts for Person Re-identification—0
Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs—0
Anomaly Detection with Test Time Augmentation and Consistency Evaluation—0
Inductive Representation Learning in Large Attributed Graphs—0
Inductive Graph Representation Learning with Quantum Graph Neural Networks—0
Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks—0
LegoNet: A Fast and Exact Unlearning Architecture—0
Learning Deep Representation with Energy-Based Self-Expressiveness for Subspace Clustering—0
Learning Deep Representation Without Parameter Inference for Nonlinear Dimensionality Reduction—0
Residual or Gate? Towards Deeper Graph Neural Networks for Inductive Graph Representation Learning—0
Inductive-Biases for Contrastive Learning of Disentangled Representations—0
Causal Representation Learning for Context-Aware Face Transfer—0
Ablation Study to Clarify the Mechanism of Object Segmentation in Multi-Object Representation Learning—0
Learning Discriminative Representations for Semantic Cross Media Retrieval—0
Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine—0
Contrastive Video Representation Learning via Adversarial Perturbations—0
Distillation Using Oracle Queries for Transformer-Based Human-Object Interaction Detection—0
Inductive and Unsupervised Representation Learning on Graph Structured Objects—0
Déjà Vu Memorization in Vision-Language Models—0
Degeneration in VAE: in the Light of Fisher Information Loss—0
Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization—0
Causal Representation Learning with Observational Grouping for CXR Classification—0
Causal Representation Learning with Generative Artificial Intelligence: Application to Texts as Treatments—0
Individual Treatment Effect Estimation Through Controlled Neural Network Training in Two Stages—0
DEFTri: A Few-Shot Label Fused Contextual Representation Learning For Product Defect Triage in e-Commerce—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