We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
: TGraphs are directed graphs with typed, attributed, and ordered nodes and edges. These properties leverage the use of graphs as models for all kinds of artifacts in the context o...
Graph transformations are one of the best known approaches for defining transformations in model-based software development. They are defined over the abstract syntax of source and...
Retiming and resynthesis transformations can be used for optimizing the area, power, and delay of sequential circuits. Even though this technique has been known for more than a de...
Rajeev K. Ranjan, Vigyan Singhal, Fabio Somenzi, R...
We design lifting-based wavelet transforms for any arbitrary communication graph in a wireless sensor network (WSN). Since transmitting raw data bits along the routing trees in WS...