104 citations · 262 across the 17 of their papers we have counts for
24 papers
Measuring disentangled generative spatio-temporal representation
Sichen Zhao, Wei Shao, Jeffrey Chan +1
Disentangled representation learning offers useful properties such as dimension reduction and interpretability, which are essential to modern deep learning approaches. Although dee…
GCCN: Global Context Convolutional Network
Ali Hamdi, Flora Salim, Du Yong Kim
In this paper, we propose Global Context Convolutional Network (GCCN) for visual recognition. GCCN computes global features representing contextual information across image patches…
Signature-Graph Networks
Ali Hamdi, Flora Salim, Du Yong Kim +1
We propose a novel approach for visual representation learning called Signature-Graph Neural Networks (SGN). SGN learns latent global structures that augment the feature representa…
PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series
Futoon M. Abushaqra, Hao Xue, Yongli Ren +1
Heterogeneity and irregularity of multi-source data sets present a significant challenge to time-series analysis. In the literature, the fusion of multi-source time-series has been…
CoSEM: Contextual and Semantic Embedding for App Usage Prediction
Yonchanok Khaokaew, Mohammad Saiedur Rahaman, Ryen W. White +1
App usage prediction is important for smartphone system optimization to enhance user experience. Existing modeling approaches utilize historical app usage logs along with a wide ra…
Evolutionary Ensemble Learning for Multivariate Time Series Prediction
Hui Song, A. K. Qin, Flora D. Salim
Multivariate time series (MTS) prediction plays a key role in many fields such as finance, energy and transport, where each individual time series corresponds to the data collected…