AdaMamba adds input-dependent frequency bases and a unified time-frequency forgetting gate to Mamba, yielding higher forecasting accuracy than prior methods on standard long-term time series benchmarks.
Fldmamba: Integrating fourier and laplace transform decomposition with mamba for enhanced time series prediction
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A Mamba-plus-attention hybrid with FFT-Laplace and TCN encoding claims state-of-the-art accuracy and efficiency on eight multivariate time-series forecasting benchmarks.
citing papers explorer
-
AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
AdaMamba adds input-dependent frequency bases and a unified time-frequency forgetting gate to Mamba, yielding higher forecasting accuracy than prior methods on standard long-term time series benchmarks.
-
UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration
A Mamba-plus-attention hybrid with FFT-Laplace and TCN encoding claims state-of-the-art accuracy and efficiency on eight multivariate time-series forecasting benchmarks.