34 citations · 62 across the 6 of their papers we have counts for
4 papers · 1 filter
An End-to-End Time Series Model for Simultaneous Imputation and Forecast
Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo +4
Time series forecasting using historical data has been an interesting and challenging topic, especially when the data is corrupted by missing values. In many industrial problem, it…
Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring
Arka Daw, Kyongmin Yeo, Anuj Karpatne +1
Inferring the source information of greenhouse gases, such as methane, from spatially sparse sensor observations is an essential element in mitigating climate change. While it is w…
Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network
Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun +2
We propose a recurrent neural network for a "model-free" simulation of a dynamical system with unknown parameters without prior knowledge. The deep learning model aims to jointly l…
Model-free prediction of noisy chaotic time series by deep learning
Kyongmin Yeo
We present a deep neural network for a model-free prediction of a chaotic dynamical system from noisy observations. The proposed deep learning model aims to predict the conditional…