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Found 3 papers, 1 papers with code
SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
This paper introduces SparseTSF, a novel, extremely lightweight model for Long-term Time Series Forecasting (LTSF), designed to address the challenges of modeling complex temporal dependencies over extended horizons with minimal computational resources.
Verified Compositional Neuro-Symbolic Control for Stochastic Systems with Temporal Logic Tasks
To the best of our knowledge, this is the first work that designs verified temporal compositions of NN controllers for unknown and stochastic systems.
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations
The beta process is employed as a prior for learning the dictionary, and this non-parametric method naturally infers an appropriate dictionary size.
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