Tom Z. Jiahao | DeepAI

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∙ 05/15/2023

Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification

Switching physical systems are ubiquitous in modern control applications...

0 Thomas Beckers, et al. ∙

∙ 04/03/2023

Leveraging Predictive Models for Adaptive Sampling of Spatiotemporal Fluid Processes

Persistent monitoring of a spatiotemporal fluid process requires data sa...

0 Sandeep Manjanna, et al. ∙

∙ 07/19/2022

Online Dynamics Learning for Predictive Control with an Application to Aerial Robots

In this work, we consider the task of improving the accuracy of dynamic ...

0 Tom Z. Jiahao, et al. ∙

∙ 09/10/2021

Learning to Swarm with Knowledge-Based Neural Ordinary Differential Equations

Understanding decentralized dynamics from collective behaviors in swarms...

0 Tom Z. Jiahao, et al. ∙

∙ 09/10/2021

KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework for Aerial Robots

In this work, we consider the problem of deriving and incorporating accu...

0 Kong Yao Chee, et al. ∙

∙ 08/07/2021

Deformable Image Registration using Neural ODEs

Deformable image registration, aiming to find spatial correspondence bet...

0 Yifan Wu, et al. ∙

∙ 10/07/2020

Learning Nonlinear Dynamics and Chaos: A Universal Framework for Knowledge-Based System Identification and Prediction

We present a universal framework for learning the behavior of dynamical ...

0 Tom Z. Jiahao, et al. ∙

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