… synthesizing stochastic logic, that is to say logic that operates on probabilistic bit streams.
In this paper, we apply the concept of stochastic logic to a reconfigurable architecture that …

… Stochastic Logic Programs (SLPs) [11] were introduced originally as a way of lifting stochastic
grammars to the level of first-order Logic Programs (LPs). Later Cussens [1] showed that …

… More specifically, we introduce neural grammar rules into stochastic definite clause … in
neural stochastic logic programming scale much better than for neural probabilistic logic programs…

… In this paper, we present a general methodology for synthesizing stochastic logic for the …
then implementing the computation with stochastic logic. The resulting logic processes serial or …

… Stochastic Logic Programs (SLPs) have been shown be a generalisation of Hidden Markov
… ), stochastic context-free grammars, and directed Bayes’ nets. A stochastic logic program …

… in first-order logic (a firstorder theory… -logical models. This paper focuses exclusively on the
parameter learning problem for a particular choice of statistical-logical model: stochastic logic …

… ordinary logic gates. On the other hand, the operation speed is not so fast since stochastic
logic … Furthermore, we propose a nonmonotonic neuron realized by stochastic logic, since the …

… potential and feasibility of handling complex matrix operations via stochastic logic circuits. …
is the binary-to-stochastic converter in Figure 2(a). Stochastic-tobinary conversion is handled …

… the information processing ability of stochastic logic neural networks, … in stochastic logic are
represented by stochastic pulse … These results suggest that stochastic logic may be useful for …

… In this section, three theoretical foundations are proposed for stochastic implementations
of polynomials. These foundations include stochastic logic implementation of polynomials …