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 4851–4900 of 10580 papers

TitleStatusHype
DIABLO: Dictionary-based Attention Block for Deep Metric Learning—0
DHOG: Deep Hierarchical Object Grouping—0
BYOLMed3D: Self-Supervised Representation Learning of Medical Videos using Gradient Accumulation Assisted 3D BYOL Framework—0
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity—0
Learning Causal Response Representations through Direct Effect Analysis—0
Intrinsic Anomaly Detection for Multi-Variate Time Series—0
DGA-Net Dynamic Gaussian Attention Network for Sentence Semantic Matching—0
Intrinsically Motivated Self-supervised Learning in Reinforcement Learning—0
INTRA: Interaction Relationship-aware Weakly Supervised Affordance Grounding—0
Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning—0
An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning—0
Adversarially learning disentangled speech representations for robust multi-factor voice conversion—0
Learning Color Representations for Low-Light Image Enhancement—0
BUTTER: A Representation Learning Framework for Bi-directional Music-Sentence Retrieval and Generation—0
Dexterity from Touch: Self-Supervised Pre-Training of Tactile Representations with Robotic Play—0
Learning by Watching: A Review of Video-based Learning Approaches for Robot Manipulation—0
Interventional Contrastive Learning with Meta Semantic Regularizer—0
BURT: BERT-inspired Universal Representation from Learning Meaningful Segment—0
A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification—0
Learning Cancer Outcomes from Heterogeneous Genomic Data Sources: An Adversarial Multi-task Learning Approach—0
Devil's Hand: Data Poisoning Attacks to Locally Private Graph Learning Protocols—0
Device Directedness with Contextual Cues for Spoken Dialog Systems—0
Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks—0
Development of a robust cascaded architecture for intelligent robot grasping using limited labelled data—0
Learning Disentangled Representations for Time Series—0
A Novel Two-Step Method for Cross Language Representation Learning—0
Interpretable time series neural representation for classification purposes—0
Developing a PET/CT Foundation Model for Cross-Modal Anatomical and Functional Imaging—0
Adversarial Learned Fair Representations using Dampening and Stacking—0
Learning by Reconstruction Produces Uninformative Features For Perception—0
Learning Canonical F-Correlation Projection for Compact Multiview Representation—0
Interpretable Sentence Representation with Variational Autoencoders and Attention—0
Interpretable representation learning of quantum data enabled by probabilistic variational autoencoders—0
Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning—0
Interpreting What Typical Fault Signals Look Like via Prototype-matching—0
Interrogating Paradigms in Self-supervised Graph Representation Learning—0
Interpretable Representation Learning of Cardiac MRI via Attribute Regularization—0
Interpretable Representation Learning from Videos using Nonlinear Priors—0
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models—0
Interventional Imbalanced Multi-Modal Representation Learning via β-Generalization Front-Door Criterion—0
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness—0
Building Large-Scale Twitter-Specific Sentiment Lexicon : A Representation Learning Approach—0
Interpretable Representation Learning for Additive Rule Ensembles—0
Detection of Fake Users in SMPs Using NLP and Graph Embeddings—0
Interpretable Node Representation with Attribute Decoding—0
TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography—0
Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation—0
Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams—0
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation—0
Interpretable Load Forecasting via Representation Learning of Geo-distributed Meteorological Factors—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