2 articles tagged with #sequence-prediction. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers have developed the Sparse Transformer, a deep neural network that achieves new performance records in sequence prediction for text, images, and sound. The model uses an improved attention mechanism that can process sequences 30 times longer than previously possible.
Researchers propose a Neuro-Symbolic Predictive Process Monitoring approach that combines deep learning with Linear Temporal Logic constraints to improve suffix prediction accuracy in business process management. The method introduces a differentiable logical loss function that ensures generated sequences satisfy both predictive accuracy and temporal logic constraints, with applications extending beyond BPM to general symbolic sequence generation tasks.
