We present an approach to hierarchically encode the topology of functions over triangulated surfaces. We describe the topology of a function by its Morse-Smale complex, a well kno...
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In...
Software components are modular and can enable post-deployment update, but their high overhead in runtime and memory is prohibitive for many embedded systems. This paper proposes ...
We develop a framework based on Bayesian model averaging to explain how animals cope with uncertainty about contingencies in classical conditioning experiments. Traditional accoun...
Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. ...