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 7451–7500 of 10580 papers

TitleStatusHype
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation—0
Progressive Multi-Modal Fusion for Robust 3D Object Detection—0
Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation—0
Progressive Residual Extraction based Pre-training for Speech Representation Learning—0
Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization—0
Learning Better Visual Representations for Weakly-Supervised Object Detection Using Natural Language Supervision—0
Disentangling Age and Identity with a Mutual Information Minimization Approach for Cross-Age Speaker Verification—0
Causality-Inspired Robustness for Nonlinear Models via Representation Learning—0
Learning Behavior Representations Through Multi-Timescale Bootstrapping—0
Learning Behavioral Representations of Human Mobility—0
Are Graph Representation Learning Methods Robust to Graph Sparsity and Asymmetric Node Information?—0
Learning Audio-guided Video Representation with Gated Attention for Video-Text Retrieval—0
Disentanglement of Correlated Factors via Hausdorff Factorized Support—0
Causality-based CTR Prediction using Graph Neural Networks—0
PSCodec: A Series of High-Fidelity Low-bitrate Neural Speech Codecs Leveraging Prompt Encoders—0
Prompt-Driven Feature Diffusion for Open-World Semi-Supervised Learning—0
Learning Attribute and Class-Specific Representation Duet for Fine-Grained Fashion Analysis—0
Implicit Causal Representation Learning via Switchable Mechanisms—0
Learning Attentive and Hierarchical Representations for 3D Shape Recognition—0
Disentanglement in Difference: Directly Learning Semantically Disentangled Representations by Maximizing Inter-Factor Differences—0
Causality-based Cross-Modal Representation Learning for Vision-and-Language Navigation—0
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation—0
Prompt Learning on Temporal Interaction Graphs—0
Prompt-Matched Semantic Segmentation—0
Action-Affect Classification and Morphing using Multi-Task Representation Learning—0
Learning a Transferable Scheduling Policy for Various Vehicle Routing Problems based on Graph-centric Representation Learning—0
Learning a State Representation and Navigation in Cluttered and Dynamic Environments—0
Learning a Joint Embedding of Multiple Satellite Sensors: A Case Study for Lake Ice Monitoring—0
Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning—0
Learning an Ensemble of Deep Fingerprint Representations—0
Learning and Retrieval from Prior Data for Skill-based Imitation Learning—0
ProS: Facial Omni-Representation Learning via Prototype-based Self-Distillation—0
Prosodic Representation Learning and Contextual Sampling for Neural Text-to-Speech—0
Protecting gender and identity with disentangled speech representations—0
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction—0
Protein-ligand binding representation learning from fine-grained interactions—0
Learning and Leveraging World Models in Visual Representation Learning—0
Causal Estimation for Text Data with (Apparent) Overlap Violations—0
A Refined Margin Distribution Analysis for Forest Representation Learning—0
Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning—0
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback—0
Prototype Memory for Large-scale Face Representation Learning—0
Disentangled Text Representation Learning with Information-Theoretic Perspective for Adversarial Robustness—0
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion—0
Learning Actionable Representations with Goal Conditioned Policies—0
Disentangled Speech Representation Learning for One-Shot Cross-lingual Voice Conversion Using β-VAE—0
Learning 6-DoF Fine-grained Grasp Detection Based on Part Affordance Grounding—0
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective—0
Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption—0
Are encoders able to learn landmarkers for warm-starting of Hyperparameter Optimization?—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