Publications associées à Graph Laplacian Mixture Model

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

The power of adaptivity in source identification with time queries on the path

Patrick Thiran, Gergely Odor, Victor Cyril L Lecomte

We study the problem of identifying the source of a stochastic diffusion process spreading on a graph based on the arrival times of the diffusion at a few queried nodes. In a graph

G=(V,E)

, an unknown source node

v^* \in V

is drawn uniformly at random, ...

2022

Graph Laplacian Mixture Model

Graph Chatbot

Chattez avec Graph Search

Distributed Graph Learning With Smooth Data Priors

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models

Graph Embedding for Retrieval

A Topological characterisation of Weisfeiler-Leman equivalence classes

Reduced representations of complexes, signals, and multifiltrations

The power of adaptivity in source identification with time queries on the path

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Representation Learning for Multi-relational Data

Sequential metric dimension for random graphs

A Topological characterisation of Weisfeiler-Leman equivalence classes

Reduced representations of complexes, signals, and multifiltrations

Graph Embedding for Retrieval

Distributed Graph Learning With Smooth Data Priors

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Representation Learning for Multi-relational Data

The power of adaptivity in source identification with time queries on the path

Sequential metric dimension for random graphs