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Found 7 papers, 2 papers with code
Faster Repeated Evasion Attacks in Tree Ensembles
Tree ensembles are one of the most widely used model classes.
Lifted Algorithms for Symmetric Weighted First-Order Model Sampling
Specifically, we prove the domain-liftability under sampling for the two-variables fragment of first-order logic with counting quantifiers in this paper, by devising an efficient sampling algorithm for this fragment that runs in time polynomial in the domain size.
On Exact Sampling in the Two-Variable Fragment of First-Order Logic
In this paper, we study the sampling problem for first-order logic proposed recently by Wang et al. -- how to efficiently sample a model of a given first-order sentence on a finite domain?
Lifted Inference with Linear Order Axiom
In this paper, we prove that adding a linear order axiom (which forces one of the predicates in $\phi$ to introduce a linear ordering of the domain elements in each model of $\phi$) on top of the counting quantifiers still permits a computation time polynomial in the domain size.
Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling
Bayesian methods of sampling from a posterior distribution are becoming increasingly popular due to their ability to precisely display the uncertainty of a model fit.
Context-Specific Likelihood Weighting
Sampling is a popular method for approximate inference when exact inference is impractical.
Neural Markov Logic Networks
We introduce neural Markov logic networks (NMLNs), a statistical relational learning system that borrows ideas from Markov logic.
