Masked Generative-Contrastive Representation Learning for Cross-Dataset EEG-Based Emotion Recognition

arXiv:2607.04139 · cs.LG · Submitted 2026-07-05 · Read on arXiv

cs.LG

Submitted: 2026-07-05

Updated: 2026-09-05

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Contrastive Learning — 32× in this paper · explained in 5 episodes
• Generalization — 23× in this paper · explained in 13 episodes
• Fine-Tuning — 18× in this paper · explained in 5 episodes
• Robustness — 11× in this paper · explained in 5 episodes
• Transformer — 10× in this paper · explained in 2 episodes
• Consistency — 9× in this paper · explained in 3 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Representation Learning — 8× in this paper · explained in 2 episodes
• Self-Supervised Learning — 8× in this paper · explained in 8 episodes
• Adjacency Matrix — 6× in this paper · explained in 1 episode
• Embeddings — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Joint Embedding Predictive Architecture — 3× in this paper
• Transfer Learning — 3× in this paper · explained in 10 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Iterative Refinement — 2× in this paper · explained in 3 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Masked Generative-Contrastive Representation Learning — 2× in this paper
• Self-Supervised Learning (SSL) — 2× in this paper · explained in 4 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Adaptive Graph — 1× in this paper · explained in 1 episode
• Affective Computing — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Decode — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Dynamic Weighting — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Masked Autoencoder (MAE) — 1× in this paper · explained in 5 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• fNIRS — 1× in this paper · explained in 2 episodes

Sources

• CLDTA: Contrastive Learning based on Diagonal Transformer Autoencoder for Cross-Dataset EEG Emotion Recognition
• Time-Series Representation Learning via Temporal and Contextual Contrasting
• Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Temporal Aware Mixed Attention-based Convolution and Transformer Network (MACTN) for EEG Emotion Recognition

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