AeroSense directly models microscopic aircraft states with masked self-attention to predict heterogeneous air traffic flows, outperforming time series baselines on real airport data.
PhaseFormer: from patches to phases for efficient and effective time series forecasting
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
FRWKV-Plus augments the FRWKV backbone with a cross-branch spectral gate and trust-gated residual correction to refine periodic handling in frequency-domain forecasting while remaining lightweight.
citing papers explorer
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From Time Series to State: Situation-Aware Modeling for Air Traffic Flow Prediction
AeroSense directly models microscopic aircraft states with masked self-attention to predict heterogeneous air traffic flows, outperforming time series baselines on real airport data.
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FRWKV+: Periodic-Aware Adaptive Gating for Frequency-Space Linear Time Series Forecasting
FRWKV-Plus augments the FRWKV backbone with a cross-branch spectral gate and trust-gated residual correction to refine periodic handling in frequency-domain forecasting while remaining lightweight.