FORECAST.ETS applies an exponential triple smoothing (ETS) algorithm to create forecasts that can include trend and seasonal ...

Abstract: Due to the complex entanglement between distributed control and distributed estimation, adaptive multiagent dynamics over leaderless directed graphs are yet not completely understood. This ...

Chemical, Applied, and Materials Physics Graduate Program, Departments of Molecular Biology and Biochemistry, Chemical and Biomolecular Engineering, Materials Science and Engineering, and Biomedical ...

Certain dogs can not only memorize the names of objects like their favorite toys, but they can also extend those labels to entirely new objects with a similar function, regardless of whether or not ...

The goal of this repository is to provide an overview of knowledge graphs in the domain of biomedicine and of resources for their construction. This is achieved in four complementary ways: A survey ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

Recently, Apers and Piddock [TQC '23] strengthened the connection between quantum walks and electrical networks via Kirchhoff's Law and Ohm's Law. In this work, we develop a new multidimensional ...

Abstract: This study explores the use of Graph Neural Networks (GNNs) to classify enzyme functions using the ENZYMES dataset, which represents proteins and their interactions as graphs. The literature ...

Department of Computer Science, Metropolitan College, Boston University, Boston, MA, United States On the other hand, using MAD offers a direct measure of deviation and is more resilient to outliers.

You’ve probably heard about the federal, state, and local governments, but how much do you really know about how they operate in Nigeria? Understanding the three tiers of government is pretty ...