Abstract: The main focus of this work is to discover naturally occurring clusters in behavioral time series, and then associate a numerical representation with every cluster, which could be used to ...
We propose S-Mamba, a Mamba-based model for time series forecasting, which delegates the extraction of inter-variate correlations and temporal dependencies to a bidirectional Mamba block and a ...
The world tried to kill Andy off but he had to stay alive to to talk about what happened with databases in 2025.
The official code for ["TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)"]. TEMPO is one of the very first open source Time Series Foundation Models for ...
Abstract: In this paper, the predefined-time cluster formation tracking (PTCFT) of the networked uncrewed surface vehicles (NUSVs) is achieved based on a hierarchical predefined-time output constraint ...
Real-world test of Apple's latest implementation of Mac cluster computing proves it can help AI researchers work using massive models, thanks to pooling memory resources over Thunderbolt 5. One month ...
A burst of low magnitude earthquakes in Northern California is just the latest in a series of earthquake clusters raising questions about whether seismic activity is increasing in the region. On ...
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