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Self-Supervised Learning

8255 directly classified papers

Papers per year

Papers

Parameter-Free Clustering via Self-Supervised Consensus Maximization AAAI 2026

Fault Diagnosis of Irregular Sequences by Adjoint Learning in Continuous-Time Model Space AAAI 2026

Dynamic Deep Graph Learning for Incomplete Multi-View Clustering with Masked Graph Reconstruction Loss AAAI 2026

Koopman Invariants as Drivers of Emergent Time-Series Clustering in Joint-Embedding Predictive Architectures AAAI 2026

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

Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation AAAI 2026

M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference AAAI 2026

Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection AAAI 2026

Adaptive and Context-rich Generative Self-supervised Learning on Graphs AAAI 2026

IdealTSF: Can Non-Ideal Data Contribute to Enhancing the Performance of Time Series Forecasting Models? AAAI 2026

Self-Supervised Learning Based on Transformed Image Reconstruction for Equivariance-Coherent Feature Representation AAAI 2026

Universal EEG Epilepsy Detection via Evidential Multi-View De-Biasing AAAI 2026

Counterfactual-based Cognitive Alignment In-Context Learning for Relation Extraction AAAI 2026

AIM: Manifold-based Data Filtering for Representation Finetuning AAAI 2026

Beyond Observations: Reconstruction Error-Guided Irregularly Sampled Time Series Representation Learning AAAI 2026

Quality-aware and Soft Consistency Driven Representation Fusion for Incomplete Multi-view Multi-label Classification AAAI 2026

Time Series Class-Incremental Learning via Confidence-guided Mask Distillation and Prototype-guided Contrastive Learning AAAI 2026

Towards Non-Stationary Time Series Forecasting with Temporal Stabilization and Frequency Differencing AAAI 2026

Continuous Vision-Language-Action Co-Learning with Semantic-Physical Alignment for Behavioral Cloning AAAI 2026

Exploring Transferability of Self-Supervised Learning by Task Conflict Calibration AAAI 2026

Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes AAAI 2026

Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction AAAI 2026

Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning AAAI 2026

Membership Inference Attack Against Large Language Model-Based Recommendation Systems: A New Distillation-Based Paradigm AAAI 2026

Cross-Sample Augmented Test-Time Adaptation for Personalized Intraoperative Hypotension Prediction AAAI 2026