5 citations · 18 across the 9 of their papers we have counts for
4 papers · 1 filter
Unraveled Multilevel Transformation Networks for Predicting Sparsely-Observed Spatiotemporal Dynamics
Priyabrata Saha, Saibal Mukhopadhyay
In this paper, we address the problem of predicting complex, nonlinear spatiotemporal dynamics when available data is recorded at irregularly-spaced sparse spatial locations. Most…
Physics-Incorporated Convolutional Recurrent Neural Networks for Source Identification and Forecasting of Dynamical Systems
Priyabrata Saha, Saurabh Dash, Saibal Mukhopadhyay
Spatio-temporal dynamics of physical processes are generally modeled using partial differential equations (PDEs). Though the core dynamics follows some principles of physics, real-…
MagNet: Discovering Multi-agent Interaction Dynamics using Neural Network
Priyabrata Saha, Arslan Ali, Burhan A. Mudassar +2
We present the MagNet, a neural network-based multi-agent interaction model to discover the governing dynamics and predict evolution of a complex multi-agent system from observatio…
Mixture of Pre-processing Experts Model for Noise Robust Deep Learning on Resource Constrained Platforms
Taesik Na, Minah Lee, Burhan A. Mudassar +3
Deep learning on an edge device requires energy efficient operation due to ever diminishing power budget. Intentional low quality data during the data acquisition for longer batter…