Publications related to Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs

Related publications (7)

Approximating Dasgupta Cost in Sublinear Time from a Few Random Seeds

Weronika Wrzos-Kaminska, Mikhail Kapralov

Testing graph cluster structure has been a central object of study in property testing since the foundational work of Goldreich and Ron [STOC’96] on expansion testing, i.e. the problem of distinguishing between a single cluster (an expander) and a graph th ...

Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing2025

DeepNC: Deep Generative Network Completion

Andreas Oliver Spitz

Most network data are collected from partially observable networks with both missing nodes and missing edges, for example, due to limited resources and privacy settings specified by users on social media. Thus, it stands to reason that inferring the missin ...

IEEE COMPUTER SOC2022

Machine Learning Models for Mycobacterium tuberculosis In Vitro Activity: Prediction and Target Visualization

Anthony Vocat

Tuberculosis (TB) is a major global health challenge, with approximately 1.4 million deaths per year. There is still a need to develop novel treatments for patients infected with Mycobacterium tuberculosis (Mtb). There have been many large-scale phenotypic ...

AMER CHEMICAL SOC2022

Simple Realizability of Complete Abstract Topological Graphs Simplified

Jan Kyncl

An abstract topological graph (briefly an AT-graph) is a pair A = (G, X) where G = (V, E) is a graph and X. E2 is a set of pairs of its edges. The AT-graph A is simply realizable if G can be drawn in the plane so that each pair of edges from X crosses exac ...

SPRINGER2020

Geostatistics of Dependent and Asymptotically Independent Extremes

Anthony Christopher Davison, Raphaël Huser, Emeric Rolland Georges Thibaud

Spatial modeling of rare events has obvious applications in the environmental sciences and is crucial when assessing the effects of catastrophic events (such as heatwaves or widespread flooding) on food security and on the sustainability of societal infras ...

Springer Heidelberg2013

Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference

Matthias Seeger

We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is provably convergent. By marrying convergent EP ideas from (O ...

2011

Minkowski sums of polytopes : combinatorics and computation

Christophe Weibel

Minkowski sums are a very simple geometrical operation, with applications in many different fields. In particular, Minkowski sums of polytopes have shown to be of interest to both industry and the academic world. This thesis presents a study of these sums, ...

EPFL2007