Representation Learning
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Benchmarks
Most implemented
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Neural Discrete Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Deep High-Resolution Representation Learning for Visual Recognition
High-Resolution Representations for Labeling Pixels and Regions
Deep High-Resolution Representation Learning for Human Pose Estimation
Papers
DGCPath: Distribution-Aware Generative Contrastive Framework for Self-supervised Path Representation Learning -- Extended Version
Due to the proliferation of vehicle trajectory data enabled by advanced sensing technologies, path representation learning has become a pivotal task in intelligent transportation systems. Although existing self-supervise…
Representation LearningContrastive LearningSelf-Supervised Lexical Representation Learning for Fast, Large-Scale Phylogenetic Inference
Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a global scale remains constrained by two factors: the labor-intensive manual annotation of cognacy judgments req…
Representation LearningContrastive LearningVectorizing Classical Tamil: Representation Learning for Verse-Commentary Pairs
We construct a corpus of 1,262 verse-commentary (urai) pairs from five Classical Tamil source sections, ranging from technical grammatical prose to modern paraphrase, and ask what information representation learning can …
Representation LearningWireless Foundation Models: State-of-the-Art and Open Challenges
Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapting them to downstream tasks. However, the rapidly growing literature r…
Representation LearningSynergistic Information Disentanglement for Omni-modal Slide Representation Learning in Computational Pathology
In computational pathology (CPath), developing omni-modal self-supervised learning (SSL) models that integrate histology, genomics, and clinical reports enables transferable representation learning for whole slide images…
Self-Supervised LearningRepresentation LearningOn the Design Fundamentals of Pixel Text Representation Learning
Text-rich visual inputs require models that can read, retrieve, and compress language directly in pixel space, yet existing pixel-text encoders struggle with fixed resolution pretraining, visual shortcut learning, weak v…
Representation LearningVisual Grounding