2 citations · 2 across the 2 of their papers we have counts for
3 papers
SpikF-GO: Spiking Fourier Graph Operators for Multivariate Time Series Forecasting
Jafar Bakhshaliyev, Niels Landwehr
Spiking Neural Networks (SNNs) have emerged as an energy-efficient alternative to conventional neural networks, demonstrating strong performance in computer vision and robotics. Mo…
Sliding-Window Reordering with Overlap Averaging: A Simple Time-Domain Augmentation for Multivariate Forecasting
Jafar Bakhshaliyev, Johannes Burchert, Niels Landwehr +1
Augmentation has become a central technique for improving deep forecasting models, but classification-style transformations tend to break the coherence between the look-back window…
Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series Forecasting
Dona Arabi, Jafar Bakhshaliyev, Ayse Coskuner +2
Data augmentation is important for improving machine learning model performance when faced with limited real-world data. In time series forecasting (TSF), where accurate prediction…