This paper focuses on automatically improving the readability of documents. We explore mechanisms relating to content control that could be used (i) by authors to improve the qual...
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
- Researchers are faced with a wide range of tasks when interacting with the literature of a scientific field. These tasks range from determining the field’s seminal documents, f...
Richard H. Fowler, Kyle Picou, Wendy Fowler, Yavuz...
Maximum entropy analysis of binary variables provides an elegant way for studying the role of pairwise correlations in neural populations. Unfortunately, these approaches suffer f...
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...