Spain

ECAI 2020

Simplifying Graph Attention Networks with Source-Target Separation

attention mechanism

graph neural networks

semi-supervised 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

Private Knowledge Transfer via Model Distillation with Generative Adversarial Networks

From Eigentrust to a Trust-measuring Algorithm in the Max-Plus Algebra

Robust Submodular Minimization with Applications to Cooperative Modeling

Minimizing and recovering from the effect of concept drift via feature selection

A Two-Stream Network with Image-to-Class Deep Metric for Few-Shot Classification

Dual Rejection Sampling for Wasserstein Auto-Encoders

Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion

Feature importance estimation with self-attention networks

Online Learning to Accelerate Neural Network Inference with Traveling Classifiers

Topological Bayesian Optimization with Persistence Diagrams

https://d3smihljt9218e.cloudfront.net/transcript/1152/subtitle/72a4abd7214e5106135b70d6c0867742.vtt

English (automatic)

Simplifying Graph Attention Networks with Source-Target Separation

Downloads

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Private Knowledge Transfer via Model Distillation with Generative Adversarial Networks

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Simplifying Graph Attention Networks with Source-Target Separation

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Next from ECAI 2020

Private Knowledge Transfer via Model Distillation with Generative Adversarial Networks

Similar lecture

PushNet: Efficient and Adaptive Neural Message Passing

Downloads