Autonomous navigation in unknown environments with obstacles remains
cha...
Position based dynamics is a powerful technique for simulating a variety...
Replanning in temporal logic tasks is extremely difficult during the onl...
In recent years, recommender systems have advanced rapidly, where embedd...
In recent years, the rapid development of deep learning has brought grea...
Since numbers in the computer are represented with a fixed number of bit...
Learning representations in the joint domain of vision and touch can imp...
Bayesian optimization (BO) has become popular for sequential optimizatio...
Many model watermarking methods have been developed to prevent valuable
...
The creation of a volumetric mesh representing the interior of an input
...
This work proposes the M3E2, a multi-task learning neural network model ...
High-quality training data play a key role in image segmentation tasks.
...
Recently, Neural Architecture Search (NAS) has been widely applied to
au...
Deep learning model (primarily convolutional networks and LSTM) for time...
This paper presents a recursive reasoning formalism of Bayesian optimiza...
A multi-layer deep Gaussian process (DGP) model is a hierarchical compos...