One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zem...
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are the most general conditions under...
—One of the most common types of functions in mathematics, physics, and engineering is a sum of products, sometimes called a partition function. After “normalization,” a sum ...
This paper proposes a non-Gaussian Markov field with a special feature: an explicit partition function. To the best of our knowledge, this is an original contribution. Moreover, th...
We prove that the translation plane and the shift plane defined by a planar partition function form an oval pair of projective planes in the sense that the planes share a line pe...
We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired...
We present a near-optimal reduction from approximately counting the cardinality of a discrete set to approximately sampling elements of the set. An important application of our wo...