Publications related to Null graph

Tree in Tree: from Decision trees to Decision Graphs

Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional dec ...

Curran Associates, Inc, (NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems)2021

A modular functional framework for the design and evaluation of multi-robot navigation

Alcherio Martinoli, Cyrill Silvan Baumann

In this work, we address the design of tightly integrated control, estimation, and allocation algorithms allowing a group of robots to move collectively. For doing so, we leverage a modular framework that allows us to define precisely the needed functional ...

2021

Partition and Code: learning how to compress graphs

Michael Bronstein, Andreas Loukas, Nikolaos Karalias, Georgios Bouritsas

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant patterns. On the other ...

2021

Adaptive majority problems for restricted query graphs and for weighted sets

Abhishek Methuku, Balázs Keszegh

Suppose that the vertices of a graph G are colored with two colors in an unknown way. The color that occurs on more than half of the vertices is called the majority color (if it exists), and any vertex of this color is called a majority vertex. We study th ...

ELSEVIER2021

How Florist Apprentices Explore Bouquet Designs: Supporting Design Space Exploration for Vocational Students

Pierre Dillenbourg, Kevin Gonyop Kim, Catharine Regina Monika Maria Oertel Genannt Bierbach

Context: Exploring the design space is an important process in a design task. In this study, we considered design space exploration for the learners in vocational education and training (VET). The goal of the study was to investigate how they explore the d ...

2021

iPool--Information-Based Pooling in Hierarchical Graph Neural Networks

Pascal Frossard, Chenglin Li, Xing Gao

With the advent of data science, the analysis of network or graph data has become a very timely research problem. A variety of recent works have been proposed to generalize neural networks to graphs, either from a spectral graph theory or a spatial perspec ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Multiscale Representation Learning of Graph Data With Node Affinity

Pascal Frossard, Chenglin Li, Xing Gao

Graph neural networks have emerged as a popular and powerful tool for learning hierarchical representation of graph data. In complement to graph convolution operators, graph pooling is crucial for extracting hierarchical representation of data in graph neu ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]

Dimitri Nestor Alice Van De Ville, Negar Kiyavash

The articles in this special section focus on graph signal processing. Generically, the networks that sustain our societies can be understood as complex systems formed by multiple nodes, where global network behavior arises from local interactions between ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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Null graph

Tree in Tree: from Decision trees to Decision Graphs

A modular functional framework for the design and evaluation of multi-robot navigation

Partition and Code: learning how to compress graphs

Adaptive majority problems for restricted query graphs and for weighted sets

Representing graphs through data with learning and optimal transport

How Florist Apprentices Explore Bouquet Designs: Supporting Design Space Exploration for Vocational Students

iPool--Information-Based Pooling in Hierarchical Graph Neural Networks

Representation Learning for Multi-relational Data

Multiscale Representation Learning of Graph Data With Node Affinity

Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]

Graph Chatbot

Chat with Graph Search

Representing graphs through data with learning and optimal transport

Adaptive majority problems for restricted query graphs and for weighted sets

Tree in Tree: from Decision trees to Decision Graphs

Partition and Code: learning how to compress graphs

A modular functional framework for the design and evaluation of multi-robot navigation

How Florist Apprentices Explore Bouquet Designs: Supporting Design Space Exploration for Vocational Students

iPool--Information-Based Pooling in Hierarchical Graph Neural Networks

Representation Learning for Multi-relational Data

Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]

Multiscale Representation Learning of Graph Data With Node Affinity