High-resolution remote sensing image semantic segmentation via multiscale context and linear self-attention
P Yin, D Zhang, W Han, J Li… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Remote sensing image semantic segmentation, which aims to realize pixel-level
classification according to the content of remote sensing images, has broad applications in …
classification according to the content of remote sensing images, has broad applications in …
Switching gaussian mixture variational rnn for anomaly detection of diverse CDN websites
L Dai, W Chen, Y Liu, A Argyriou, C Liu… - … -IEEE Conference on …, 2022 - ieeexplore.ieee.org
To conduct service quality management of industry devices or Internet infrastructures,
various deep learning approaches have been used for extracting the normal patterns of …
various deep learning approaches have been used for extracting the normal patterns of …
Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting
M Wang, W Chen, B Chen - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
The forecasting of Multivariate Time Series (MTS) has long been an important but
challenging task. Due to the non-stationary problem across long-distance time steps …
challenging task. Due to the non-stationary problem across long-distance time steps …
Infinite switching dynamic probabilistic network with Bayesian nonparametric learning
To model sequentially observed multivariate nonstationary count data, we propose a
switching Poisson-gamma dynamical systems (SPGDS), a dynamic probabilistic network …
switching Poisson-gamma dynamical systems (SPGDS), a dynamic probabilistic network …
Negative-Binomial Randomized Gamma Markov Processes for Heterogeneous Overdispersed Count Time Series
Modeling count-valued time series has been receiving increasing attention since count time
series naturally arise in physical and social domains. Poisson gamma dynamical systems …
series naturally arise in physical and social domains. Poisson gamma dynamical systems …
Poisson-Gamma Dynamical Systems with Non-Stationary Transition Dynamics
Bayesian methodologies for handling count-valued time series have gained prominence
due to their ability to infer interpretable latent structures and to estimate uncertainties, and …
due to their ability to infer interpretable latent structures and to estimate uncertainties, and …
VARIATIONAL ADAPTIVE GRAPH TRANSFORMER FOR MULTIVARIATE TIME SERIES MODELING
L Tian, W Chen, B Chen, M Wang, L Dai, BL Sun… - openreview.net
Multivariate time series (MTS) are widely collected by large-scale complex systems, such as
internet services, IT infrastructures, and wearable devices. The modeling of MTS has long …
internet services, IT infrastructures, and wearable devices. The modeling of MTS has long …