Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density esti...
Laura M. Smith, Matthew S. Keegan, Todd Wittman, G...
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Programmability is an increasingly important barrier to the deployment of multi-robot systems, as no prior approach allows routine composition and reuse of general aggregate behavi...
This demonstration presents Crescando, an implementation of a distributed relational table that guarantees predictable response time on unpredictable workloads. In Crescando, data...
Georgios Giannikis, Philipp Unterbrunner, Jeremy M...
We present a novel framework to estimate protein-protein (PPI) and domain-domain (DDI) interactions based on a belief propagation estimation method that efficiently computes inter...
Faruck Morcos, Marcin Sikora, Mark S. Alber, Dale ...