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 8451–8500 of 10580 papers

TitleStatusHype
Enhancing Word-Level Semantic Representation via Dependency Structure for Expressive Text-to-Speech Synthesis—0
Instance-Conditioned GAN Data Augmentation for Representation Learning—0
Instance-Aware Representation Learning and Association for Online Multi-Person Tracking—0
Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification—0
Instance-Aware Graph Prompt Learning—0
InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction—0
Dental CLAIRES: Contrastive LAnguage Image REtrieval Search for Dental Research—0
InProC: Industry and Product/Service Code Classification—0
Density-Based Bonuses on Learned Representations for Reward-Free Exploration in Deep Reinforcement Learning—0
Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning—0
A Novel Generative Model with Causality Constraint for Mitigating Biases in Recommender Systems—0
Inpatient2Vec: Medical Representation Learning for Inpatients—0
INoD: Injected Noise Discriminator for Self-Supervised Representation Learning in Agricultural Fields—0
Dense Semantic Contrast for Self-Supervised Visual Representation Learning—0
Injecting Lexical Contrast into Word Vectors by Guiding Vector Space Specialisation—0
Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks—0
Morphological Network: How Far Can We Go with Morphological Neurons?—0
Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation—0
InfoVAEGAN : learning joint interpretable representations by information maximization and maximum likelihood—0
InfoStyler: Disentanglement Information Bottleneck for Artistic Style Transfer—0
InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization—0
Informative Robust Causal Representation for Generalizable Deep Learning—0
Dense Contrastive Visual-Linguistic Pretraining—0
Towards Better Understanding of Disentangled Representations via Mutual Information—0
Informative GANs via Structured Regularization of Optimal Transport—0
Information Theory-Guided Heuristic Progressive Multi-View Coding—0
DenoMAE2.0: Improving Denoising Masked Autoencoders by Classifying Local Patches—0
Information Theory-Guided Heuristic Progressive Multi-View Coding—0
Information-Theoretic Representation Learning for Positive-Unlabeled Classification—0
Information propagation dynamics in Deep Graph Networks—0
Denoising with a Joint-Embedding Predictive Architecture—0
Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder—0
Hierarchical Aligned Multimodal Learning for NER on Tweet Posts—0
A Conjoint Graph Representation Learning Framework for Hypertension Comorbidity Risk Prediction—0
Addressing Feature Suppression in Unsupervised Visual Representations—0
Information Potential Auto-Encoders—0
Entropy Minimization In Emergent Languages—0
Denoising Cosine Similarity: A Theory-Driven Approach for Efficient Representation Learning—0
Bridging CNNs, RNNs, and Weighted Finite-State Machines—0
Information Bottleneck Inspired Method For Chat Text Segmentation—0
Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning—0
Information-based Disentangled Representation Learning for Unsupervised MR Harmonization—0
Denoising Autoregressive Representation Learning—0
Bridging Brain Signals and Language: A Deep Learning Approach to EEG-to-Text Decoding—0
Information-Aware Time Series Meta-Contrastive Learning—0
InfoGCL: Information-Aware Graph Contrastive Learning—0
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models—0
Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks—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