MedMamba introduces a principle-guided bidirectional multi-scale Mamba model that outperforms prior methods on EEG, ECG, and activity classification benchmarks while delivering 4.6x inference speedup.
Multi-resolution time-series transformer for long-term forecasting
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A per-customer multi-head attention transformer predicts data center SLA breaches 30 minutes ahead by encoding rules as JSON for training and emitting role-specific outputs for finance, operations, and compliance.
citing papers explorer
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MedMamba: Recasting Mamba for Medical Time Series Classification
MedMamba introduces a principle-guided bidirectional multi-scale Mamba model that outperforms prior methods on EEG, ECG, and activity classification benchmarks while delivering 4.6x inference speedup.
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A Multi-Head Attention Approach for SLA Compliance Monitoring in Data Centers
A per-customer multi-head attention transformer predicts data center SLA breaches 30 minutes ahead by encoding rules as JSON for training and emitting role-specific outputs for finance, operations, and compliance.