We describe a generative model for graph edges under specific degree distributions which admits an exact and efficient inference method for recovering the most likely structure. T...
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
Background: Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem ...
Pierre Geurts, Nizar Touleimat, Marie Dutreix, Flo...