In safe MDP planning, a cost function based on the current state and act...
Experimental sciences have come to depend heavily on our ability to orga...
Deep learning has been actively applied to time-series forecasting, lead...
Modern software systems rely on mining insights from business sensitive ...
Recent advances in deep learning have enabled optimization of deep react...
Existing approaches for embedding unobtrusive tags inside 3D objects req...
Deep learning has been actively studied for time series forecasting, and...
Transformers have been actively studied for time-series forecasting in r...
We introduce an algorithm for computing geodesics on sampled manifolds t...
Solving multiagent problems can be an uphill task due to uncertainty in ...
In urban environments, supply resources have to be constantly matched to...
Decentralized (PO)MDPs provide an expressive framework for sequential
de...
Stochastic network design is a general framework for optimizing network
...
Decentralized POMDPs provide an expressive framework for multi-agent
seq...
Computing maximum a posteriori (MAP) estimation in graphical models is a...