Spain

ECAI 2020

A Lagrangian Approach to Information Propagation in Graph Neural Networks

lagrangian

constrained optimization

information diffusion

graph representation learning

graph neural networks

machine learning

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers. 
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities. This includes talks to attend in person, talks to attend remotely, breaks with colleagues and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).

In order to access this site, you need to register. If you haven't already, please register [here](https://aaai.org/Conferences/AAAI-23/registration/).


AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

technical paper

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

A Compact Spectral Descriptor for Shape Deformations

Coulomb Autoencoders

A Knowledge-based System for the Dynamic Generation and Classification of Novel Contents in Multimedia Broadcasting

SETNet : A Novel Semi-Supervised Approach for Semantic Parsing

A Knowledge-driven Approach to Explaining Black-box Models

Accounting for Observer’s Partial Observability in Stochastic Goal Recognition Design: Messing with the Marauder’s Map

Learning Conjunctive Information   of Signals in Multi-sensor Systems

Tree search for the Sequential Ordering Problem

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

Multi-Stage Transfer Learning with an Application to Selection Process

https://d3smihljt9218e.cloudfront.net/transcript/1179/subtitle/2c947b91830273b3f0b675be4614c935.vtt

English (automatic)

A Lagrangian Approach to Information Propagation in Graph Neural Networks

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A Compact Spectral Descriptor for Shape Deformations

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Generalizing Downsampling from Regular Data to Graphs

A Lagrangian Approach to Information Propagation in Graph Neural Networks

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Next from ECAI 2020

A Compact Spectral Descriptor for Shape Deformations

Similar lecture

Generalizing Downsampling from Regular Data to Graphs

Downloads