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 7101–7150 of 10580 papers

TitleStatusHype
Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding—0
Divide and Conquer Self-Supervised Learning for High-Content Imaging—0
Learning Hierarchical Structures On-The-Fly with a Recurrent-Recursive Model for Sequences—0
Parameter Efficient Multimodal Transformers for Video Representation Learning—0
Diversifying Joint Vision-Language Tokenization Learning—0
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition—0
Parameterization of Hypercomplex Multiplications—0
Parameterized context windows in Random Indexing—0
Are You A Risk Taker? Adversarial Learning of Asymmetric Cross-Domain Alignment for Risk Tolerance Prediction—0
Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction—0
Learning Hierarchical Graph Representation for Image Manipulation Detection—0
Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection—0
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior—0
Learning Hidden Markov Models with Distributed State Representations for Domain Adaptation—0
DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization—0
CDPS: Constrained DTW-Preserving Shapelets—0
Revisiting the role of heterophily in graph representation learning: An edge classification perspective—0
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects—0
Diversified Node Sampling based Hierarchical Transformer Pooling for Graph Representation Learning—0
Learning Graph Search Heuristics—0
Learning by Sampling and Compressing: Efficient Graph Representation Learning with Extremely Limited Annotations—0
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning—0
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network—0
Are Word Embedding Methods Stable and Should We Care About It?—0
Learning Good Policies By Learning Good Perceptual Models—0
Learning Global Object-Centric Representations via Disentangled Slot Attention—0
Learning Geospatial Region Embedding with Heterogeneous Graph—0
div2vec: Diversity-Emphasized Node Embedding—0
Learning Geometric Invariant Features for Classification of Vector Polygons with Graph Message-passing Neural Network—0
C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation—0
PARTS: Unsupervised Segmentation With Slots, Attention and Independence Maximization—0
Passenger Mobility Prediction via Representation Learning for Dynamic Directed and Weighted Graph—0
A Review on Deep Learning Techniques for Video Prediction—0
PatchFormer: A neural architecture for self-supervised representation learning on images—0
AEMIM: Adversarial Examples Meet Masked Image Modeling—0
Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data—0
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training—0
Distribution Preserving Graph Representation Learning—0
Learning Generalizable Dexterous Manipulation from Human Grasp Affordance—0
Learning Future Representation with Synthetic Observations for Sample-efficient Reinforcement Learning—0
A Review of Text Style Transfer using Deep Learning—0
Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency—0
Learning From the Experience of Others: Approximate Empirical Bayes in Neural Networks—0
Learning from Streaming Video with Orthogonal Gradients—0
Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis—0
Pathology Report Generation and Multimodal Representation Learning for Cutaneous Melanocytic Lesions—0
CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification—0
Learning from Multiview Correlations in Open-Domain Videos—0
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations—0
A Review of Mechanistic Models of Event Comprehension—0
Show:102550
← PrevPage 143 of 212Next →
All datasetsSciDocsAnimals-10CIFAR10Circle DataSports10

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