Spain

ECAI 2020

Learning Kernel-based Embeddings in Graph Neural Networks

transfer/adaptation/multi-task learning

kernel methods

graph neural networks

deep learning

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.

technical paper

Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation

Dynamic Epistemic Logic Games with Epistemic Temporal Goals

New measures of inclusion between fuzzy sets in terms of the φ-index of inclusion

Representing and Reducing Uncertainty for Enumerating the Belief Space to Improve Endgame Play in Skat

Ontology Focusing: Knowledge-enriched Databases on Demand

A Hash Learning Framework for Search-Oriented Knowledge Graph Embedding

Link Prediction by Analyzing Common Neighbors Based Subgraphs using Convolutional Neural Network

Many-Objective Problems Are Not Always Difficult for Pareto Dominance-Based Evolutionary Algorithms

Pruning CNN's with linear filter ensembles

On the Relation between Claim-augmented Argumentation Frameworks and Collective Attacks

https://d3smihljt9218e.cloudfront.net/transcript/1246/subtitle/21faab4b5c5607f743e88953cc6f3d04.vtt

English (automatic)

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Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation

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PushNet: Efficient and Adaptive Neural Message Passing

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Next from ECAI 2020

Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation

Similar lecture

PushNet: Efficient and Adaptive Neural Message Passing

Downloads