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Found 5 papers, 4 papers with code
$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
Probabilistic Time Series Forecasting (PTSF) plays a crucial role in decision-making across various fields, including economics, energy, and transportation.
MM-Path: Multi-modal, Multi-granularity Path Representation Learning -- Extended Version
In this paper, we propose a novel Multi-modal, Multi-granularity Path Representation Learning Framework (MM-Path), which can learn a generic path representation by integrating modalities from both road paths and image paths.
DiffImp: Efficient Diffusion Model for Probabilistic Time Series Imputation with Bidirectional Mamba Backbone
Probabilistic time series imputation has been widely applied in real-world scenarios due to its ability to estimate uncertainty of imputation results.
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-Resolution
In recent years, there has been an increasing demand for real-time super-resolution networks on mobile devices.
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report
While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints.
