Learning domain-invariant representations is a major task of out-of-distribution generalization. To address this issue, recent efforts have taken into accounting causality, aiming at learning the causal factors with regard to tasks. However, extending existing generalization methods for adapting non-stationary time series may be ineffective, because they fail model underlying due temporal-domai...

In the analysis of logic programs, abstract domains for detecting sharing and linearity information are widely used. Devising abstract unification algorithms for such domains has proved to be rather hard. As a consequence, only correct algorithms are available at the moment, which partially exploit the information conveyed by the abstract domains. In this paper, we define a new (infinite) domai...

There are many applications where precise mode analysis is required. However, within the framework of abstract interpretation, the precision of an analyser depends, in part, on the expressiveness of the abstract domain and its associated abstraction function. This paper considers abstract domains for polymorphically typed logic programs where each non-variable symbol is explicitly typed. We sho...

This paper addresses the problem of abstracting a set of affine transformers ÝÑv 1 ÝÑv C ÝÑ d , where ÝÑv and ÝÑv 1 represent the prestate and post-state, respectively. We introduce a framework to harness any base abstract domain B in an abstract domain of affine transformations. Abstract domains are usually used to define constraints on the variables of a program. In this paper, however, abstr...