We present egglog, a fixpoint reasoning system that unifies Datalog and equality saturation
(EqSat). Like Datalog, egglog supports efficient incremental execution, cooperating …

Tensor programs often need to process large tensors (vectors, matrices, or higher order
tensors) that require a specialized storage format for their memory layout. Several such …

Optimizing the expected values of probabilistic processes is a central problem in computer
science and its applications, arising in fields ranging from artificial intelligence to operations …

We present Lilac, a separation logic for reasoning about probabilistic programs where
separating conjunction captures probabilistic independence. Inspired by an analogy with …

Equality graphs (e-graphs) are used to compactly represent equivalence classes of terms in
symbolic reasoning systems. Beyond their original roots in automated theorem proving, e …

Edge computing has gained significant traction in recent years, promising enhanced
efficiency by integrating artificial intelligence capabilities at the edge. While the focus has …

Probabilistic couplings are the foundation for many probabilistic relational program logics
and arise when relating random sampling statements across two programs. In relational …

Datalog has gained prominence in program analysis due to its expressiveness and ease of
use. Its generic fixpoint resolution algorithm over relational domains simplifies the …

Overparameterized models in regression analysis are often harder to interpret and can be
harder to fit because of ill-conditioning. Genetic programming is prone to overparameterized …

Probabilistic programming languages are used to write probabilistic models to make
probabilistic inferences. A number of rigorous semantics have recently been proposed that …