Publications associées à Mixed graph

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero, Mohan Vamsi Nallapareddy

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

PMLR2024

The connection of the acyclic disconnection and feedback arc sets - On an open problem of Figueroa et al

Lukas Fritz Felix Vogl

We examine the connection of two graph parameters, the size of a minimum feedback arcs set and the acyclic disconnection. A feedback arc set of a directed graph is a subset of arcs such that after deletion the graph becomes acyclic. The acyclic disconnecti ...

Elsevier2024

Motif Cut Sparsifiers

Mikhail Kapralov, Mikhail Makarov, Jakab Tardos

A motif is a frequently occurring subgraph of a given directed or undirected graph G (Milo et al.). Motifs capture higher order organizational structure of G beyond edge relationships, and, therefore, have found wide applications such as in graph clusterin ...

IEEE COMPUTER SOC2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models

Negar Kiyavash, Ehsan Mokhtarian, Saber Salehkaleybar

We study experiment design for unique identification of the causal graph of a system where the graph may contain cycles. The presence of cycles in the structure introduces major challenges for experiment design as, unlike acyclic graphs, learning the skele ...

2023

Belief Control Strategies for Interactions Over Weakly-Connected Graphs

Ali H. Sayed, Bicheng Ying

In diffusion social learning over weakly-connected graphs, it has been shown recently that influential agents shape the beliefs of non-influential agents. This paper analyzes this mechanism more closely and addresses two main questions. First, the article ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Localized Spectral Graph Filter Frames: A Unifying Framework, Survey of Design Considerations, and Numerical Comparison

David Shuman

A major line of work in graph signal processing [2] during the past 10 years has been to design new transform methods that account for the underlying graph structure to identify and exploit structure in data residing on a connected, weighted, undirected gr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Learning Graph Influence From Social Interactions

Ali H. Sayed, Virginia Bordignon, Augusto José Rabelo Almeida Santos

In social learning, agents form their opinions or beliefs about certain hypotheses by exchanging local information. This work considers the recent paradigm of weak graphs, where the network is partitioned into sending and receiving components, with the for ...

IEEE2020

Graph Laplacian Mixture Model

Pascal Frossard, Hermina Petric Maretic

Graph learning methods have recently been receiving increasing interest as means to infer structure in datasets. Most of the recent approaches focus on different relationships between a graph and data sample distributions, mostly in settings where all avai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Distributed Coloring of Graphs with an Optimal Number of Colors

Etienne Michel François Bamas

This paper studies sufficient conditions to obtain efficient distributed algorithms coloring graphs optimally (i.e. with the minimum number of colors) in the LOCAL model of computation. Most of the work on distributed vertex coloring so far has focused on ...

SCHLOSS DAGSTUHL, LEIBNIZ CENTER INFORMATICS2019