2D forward-looking sonar is a crucial sensor for underwater robotic
perc...
Imaging sonar produces clear images in underwater environments, independ...
Retrieving the missing dimension information in acoustic images from 2D
...
Video deblurring is a highly under-constrained problem due to the spatia...
Compared to traditional imitation learning methods such as DAgger and DA...
We introduce the framework of continuous-depth graph neural networks (GN...
Effective control and prediction of dynamical systems often require
appr...
We detail a novel class of implicit neural models. Leveraging time-paral...
We systematically develop a learning-based treatment of stochastic optim...
At modern construction sites, utilizing GNSS (Global Navigation Satellit...
We introduce optimal energy shaping as an enhancement of classical
passi...
Continuous-depth learning has recently emerged as a novel perspective on...
The infinite-depth paradigm pioneered by Neural ODEs has launched a
rena...
In this study, we present a method for all-around depth estimation from
...
We introduce a provably stable variant of neural ordinary differential
e...
Continuous deep learning architectures have recently re-emerged as varia...
We extend the framework of graph neural networks (GNN) to continuous tim...
Neural networks are discrete entities: subdivided into discrete layers a...