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 2901–2950 of 10580 papers

TitleStatusHype
Adaptive Part Learning for Fine-Grained Generalized Category Discovery: A Plug-and-Play Enhancement—0
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion—0
Contrastive Decoupled Representation Learning and Regularization for Speech-Preserving Facial Expression Manipulation—0
The Causal Structure of Domain Invariant Supervised Representation Learning—0
Contrastive Data and Learning for Natural Language Processing—0
Contrastive Cross-Modal Knowledge Sharing Pre-training for Vision-Language Representation Learning and Retrieval—0
Align Voting Behavior with Public Statements for Legislator Representation Learning—0
Contrastive Continual Learning with Feature Propagation—0
Adaptive Online Incremental Learning for Evolving Data Streams—0
Bailing-TTS: Chinese Dialectal Speech Synthesis Towards Human-like Spontaneous Representation—0
Few-shot Weakly-supervised Cybersecurity Anomaly Detection—0
Fill in the Gap! Combining Self-supervised Representation Learning with Neural Audio Synthesis for Speech Inpainting—0
Spectral-Aware Augmentation for Enhanced Graph Representation Learning—0
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images—0
Contrastive Classification and Representation Learning with Probabilistic Interpretation—0
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model—0
AlignMix: Improving representations by interpolating aligned features—0
Few-Shot Meta Learning for Recognizing Facial Phenotypes of Genetic Disorders—0
Learning Video Representations using Contrastive Bidirectional Transformer—0
Contrastive Attention Maps for Self-Supervised Co-Localization—0
Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing—0
Few-Shot Learning via Learning the Representation, Provably—0
Contrastive Approach to Prior Free Positive Unlabeled Learning—0
Augment, Drop & Swap: Improving Diversity in LLM Captions for Efficient Music-Text Representation Learning—0
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks—0
NEXT: A Neural Network Framework for Next POI Recommendation—0
ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration—0
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices—0
Alignment and stability of embeddings: measurement and inference improvement—0
Few-Shot Learning on Graphs—0
Learning Transferable Adversarial Robust Representations via Multi-view Consistency—0
ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision—0
Continuous-time Graph Representation with Sequential Survival Process—0
Augmentation Invariant Manifold Learning—0
Continuous Tensor Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems—0
Augmentation-based Unsupervised Cross-Domain Functional MRI Adaptation for Major Depressive Disorder Identification—0
Aligning Robot and Human Representations—0
Continuous Histogram Loss: Beyond Neural Similarity—0
Adaptive Multi-Neighborhood Attention based Transformer for Graph Representation Learning—0
Continuous Adversarial Text Representation Learning for Affective Recognition—0
An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning—0
Deep Representation Learning with an Information-theoretic Loss—0
Continual Vision-Language Representation Learning with Off-Diagonal Information—0
Continual Unsupervised Representation Learning—0
Continual State Representation Learning for Reinforcement Learning using Generative Replay—0
Aligning Multimodal Representations through an Information Bottleneck—0
Audio-visual Representation Learning for Anomaly Events Detection in Crowds—0
Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer—0
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks—0
Continual Lifelong Causal Effect Inference with Real World Evidence—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