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 8051–8100 of 10580 papers

TitleStatusHype
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection—0
Beyond H&E: Unlocking Pathological Insights with Polarization via Self-supervised Learning—0
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency—0
NodeSig: Binary Node Embeddings via Random Walk Diffusion—0
Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving—0
Saliency Guided Contrastive Learning on Scene Images—0
Sample-efficient Adversarial Imitation Learning—0
Distributed Representations of Entities in Open-World Knowledge Graphs—0
GRU-TV: Time- and velocity-aware GRU for patient representation on multivariate clinical time-series data—0
Road Network Representation Learning with the Third Law of Geography—0
Decentralized Complete Dictionary Learning via ^4-Norm Maximization—0
Robo360: A 3D Omnispective Multi-Material Robotic Manipulation Dataset—0
Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphs—0
Growing Representation Learning—0
Growing ecosystem of deep learning methods for modeling proteinx2013protein interactions—0
Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction—0
Deblurring Neural Radiance Fields with Event-driven Bundle Adjustment—0
Robust Anchor Embedding for Unsupervised Video Person Re-Identification in the Wild—0
A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions—0
Robust and Controllable Object-Centric Learning through Energy-based Models—0
Group-wise Deep Co-saliency Detection—0
Debiasing Pretrained Text Encoders by Paying Attention to Paying Attention—0
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning—0
Graph Embedding with Rich Information through Heterogeneous Network—0
RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning—0
DotSCN: Group Re-identification via Domain-Transferred Single and Couple Representation Learning—0
Robust contrastive learning and nonlinear ICA in the presence of outliers—0
Robust Cross-Modal Representation Learning with Progressive Self-Distillation—0
Debiasing Graph Representation Learning based on Information Bottleneck—0
Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection—0
ROBUST DISCRIMINATIVE REPRESENTATION LEARNING VIA GRADIENT RESCALING: AN EMPHASIS REGULARISATION PERSPECTIVE—0
Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model—0
Group Generalized Mean Pooling for Vision Transformer—0
Robust facial expression recognition with global‑local joint representation learning—0
Group-disentangled Representation Learning with Weakly-Supervised Regularization—0
Robust Graph Neural Networks for Stability Analysis in Dynamic Networks—0
De-biased Representation Learning for Fairness with Unreliable Labels—0
Robust Graph Structure Learning under Heterophily—0
Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning—0
Robust Invariant Representation Learning by Distribution Extrapolation—0
Learning Robust Data Representation: A Knowledge Flow Perspective—0
Robust Large-Margin Learning in Hyperbolic Space—0
An Attention-Driven Approach of No-Reference Image Quality Assessment—0
Robust Locality-Aware Regression for Labeled Data Classification—0
Robust Machine Learning by Transforming and Augmenting Imperfect Training Data—0
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training—0
Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices—0
Analysis of Spatial augmentation in Self-supervised models in the purview of training and test distributions—0
Robust Multi-view Representation Learning—0
S^2ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning—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