Add to ORKGAbstract. We present an approach to probabilistic analysis which is based on program semantics and exploits the mathematical properties of the semantical operators to ensure a form of optimality for the analysis. As in the algorithmic setting, where the analysis results are used the help the design of efficient algorithms, the purposes of our framework are to offer static analysis techniques usable for resource optimisation.
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
In this paper we start by reviewing both classical and probabilistic/quantitative approaches to prog...
This paper provides a survey of recent work on adapting techniques for program analysis to compute p...
We present an approach to probabilistic analysis which is based on program semantics and exploits th...
The aims of these lecture notes are two-fold: (i) we investigate the relation between the operationa...
We present a semantics-based technique for analysing probabilistic properties of imperative programs...
AbstractWe present a semantics-based technique for analysing probabilistic properties of imperative ...
Abstract. For a simple probabilistic language we present a semantics based on linear operators on in...
We outline a general purpose framework for black-box marginal maximum a pos- teriori estimation of p...
Abstract. We provide a HOL formalisation for analysing expected time bounds for probabilistic progra...
Abstract. Having a precise yet sound abstraction of the inputs of nu-merical programs is important t...
Probabilistic programs [6] are sequential programs, written in languages like C, Java, Scala, or ML,...
We present a new semantics sensitive sampling algorithm for probabilistic pro-grams, which are “usua...
We present a formal framework for syntax directed probabilistic program analysis. Our focus is on pr...
The work is supported by the EPSRC. Abstract. In this paper we show how quantitative program logic [...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
In this paper we start by reviewing both classical and probabilistic/quantitative approaches to prog...
This paper provides a survey of recent work on adapting techniques for program analysis to compute p...
We present an approach to probabilistic analysis which is based on program semantics and exploits th...
The aims of these lecture notes are two-fold: (i) we investigate the relation between the operationa...
We present a semantics-based technique for analysing probabilistic properties of imperative programs...
AbstractWe present a semantics-based technique for analysing probabilistic properties of imperative ...
Abstract. For a simple probabilistic language we present a semantics based on linear operators on in...
We outline a general purpose framework for black-box marginal maximum a pos- teriori estimation of p...
Abstract. We provide a HOL formalisation for analysing expected time bounds for probabilistic progra...
Abstract. Having a precise yet sound abstraction of the inputs of nu-merical programs is important t...
Probabilistic programs [6] are sequential programs, written in languages like C, Java, Scala, or ML,...
We present a new semantics sensitive sampling algorithm for probabilistic pro-grams, which are “usua...
We present a formal framework for syntax directed probabilistic program analysis. Our focus is on pr...
The work is supported by the EPSRC. Abstract. In this paper we show how quantitative program logic [...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
In this paper we start by reviewing both classical and probabilistic/quantitative approaches to prog...
This paper provides a survey of recent work on adapting techniques for program analysis to compute p...