← Core Methods

Machine Learning › Core Methods ›

Representation Learning

18863 directly classified papers

Papers per year

Papers

High-Pass Matters: Theoretical Insights and Sheaflet-Based Design for Hypergraph Neural Networks AAAI 2026

Permutation Equivariant Framelet-based Hypergraph Neural Networks AAAI 2026

Dynamic Semantic Tokenization for Time Series via Elastic Sampling on Physics-aware Perception AAAI 2026

Cross Modal Fine-grained Alignment via Granularity-aware and Region-uncertain Modeling AAAI 2026

A Unified Shape-Aware Foundation Model for Time Series Classification AAAI 2026

Adapt Before Continual Learning AAAI 2026

Semantic-Aware Feature Enhancement for Partial Label Learning AAAI 2026

RankList – a Listwise Preference Learning Framework for Predicting Subjective Preferences AAAI 2026

Graph Contrastive Learning with Balanced Hard Negatives and Fine-grained Semantic-aware Positives AAAI 2026

MUG: Meta-path-aware Universal Heterogeneous Graph Pre-Training AAAI 2026

Learning to Rank: How GNNs Solve Max-Clique and Sparse PCA AAAI 2026

MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data AAAI 2026

COGS: A Causal Representation Learning Framework for Out-of-Distribution Generalization in Time Series AAAI 2026

Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering AAAI 2026

Discriminative Graph Embedding Framework via Label-Free Marginal Fisher Analysis AAAI 2026

Adaptive Riemannian Graph Neural Networks AAAI 2026

Decoupled Spatiotemporal Forecasting from Extreme Sparse Observations via Quantized Latent Space AAAI 2026

DIN: Dual Impulse Network for Multi-view Representation Learning AAAI 2026

Multi-modal Dynamic Proxy Learning for Personalized Multiple Clustering AAAI 2026

HiNCoT: Hierarchical Nonlinear Continuous Transform-based Tensor Representation for Multi-Dimensional Data Recovery AAAI 2026

Learning Adaptive and Expandable Mixture Model for Continual Learning AAAI 2026

R-Tuning: Wavelet-Decomposed Replay and Semantic Alignment for Continual Adaptation of Pretrained Time-Series Models AAAI 2026

FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting AAAI 2026

QuMAB: Query-based Multi-annotator Behavior Pattern Learning AAAI 2026

SCIR: A Self-Correcting Iterative Refinement Framework for Enhanced Information Extraction Based on Schema AAAI 2026