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 3751–3800 of 10580 papers

TitleStatusHype
Collaboration of Pre-trained Models Makes Better Few-shot Learner—0
GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training—0
Hierarchical Transformer for Scalable Graph Learning—0
HierPromptLM: A Pure PLM-based Framework for Representation Learning on Heterogeneous Text-rich Networks—0
Gaussian2Scene: 3D Scene Representation Learning via Self-supervised Learning with 3D Gaussian Splatting—0
Gaussian Masked Autoencoders—0
High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text-attributed Graphs—0
HIN-RNN: A Graph Representation Learning Neural Network for Fraudster Group Detection With No Handcrafted Features—0
How benign is benign overfitting?—0
Information-based Disentangled Representation Learning for Unsupervised MR Harmonization—0
Embedded Representation Learning Network for Animating Styled Video Portrait—0
Coordinated Transformer with Position \& Sample-aware Central Loss for Anatomical Landmark Detection—0
Embedded Mean Field Reinforcement Learning for Perimeter-defense Game—0
GCN-based Multi-task Representation Learning for Anomaly Detection in Attributed Networks—0
CoLiDR: Concept Learning using Aggregated Disentangled Representations—0
Embed Any NeRF: Graph Meta-Networks for Neural Tasks on Arbitrary NeRF Architectures—0
A survey on knowledge-enhanced multimodal learning—0
GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs—0
GCN-SL: Graph Convolutional Network with Structure Learning for Disassortative Graphs—0
Hierarchical Representation Learning for Kinship Verification—0
Hierarchical Representation Learning for Markov Decision Processes—0
Autonomous Goal Exploration using Learned Goal Spaces for Visuomotor Skill Acquisition in Robots—0
GenCAD: Image-Conditioned Computer-Aided Design Generation with Transformer-Based Contrastive Representation and Diffusion Priors—0
GenDistiller: Distilling Pre-trained Language Models based on Generative Models—0
A Geometry-Aware Algorithm to Learn Hierarchical Embeddings in Hyperbolic Space—0
Elucidating and Overcoming the Challenges of Label Noise in Supervised Contrastive Learning—0
ELiTe: Efficient Image-to-LiDAR Knowledge Transfer for Semantic Segmentation—0
Gene-Level Representation Learning via Interventional Style Transfer in Optical Pooled Screening—0
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide—0
Hierarchical Query Classification in E-commerce Search—0
Core-Periphery Principle Guided State Space Model for Functional Connectome Classification—0
General Item Representation Learning for Cold-start Content Recommendations—0
CoKe: Localized Contrastive Learning for Robust Keypoint Detection—0
Co-Representation Learning For Classification and Novel Class Detection via Deep Networks—0
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources—0
Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing—0
elBERto: Self-supervised Commonsense Learning for Question Answering—0
Generalizable task representation learning from human demonstration videos: a geometric approach—0
Correlated Attention in Transformers for Multivariate Time Series—0
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer—0
Hierarchical Prototype Network for Continual Graph Representation Learning—0
Generalization Analysis for Contrastive Representation Learning—0
Generalization Analysis for Contrastive Representation Learning under Non-IID Settings—0
Generalization Analysis for Deep Contrastive Representation Learning—0
Elastic Information Bottleneck—0
A Survey on Graph Representation Learning Methods—0
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage—0
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects—0
A Geometric Perspective on Optimal Representations for Reinforcement Learning—0
Eight challenges in developing theory of intelligence—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